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A Step Closer to Comprehensive Answers: Constrained Multi-Stage Question Decomposition with Large Language Models

https://arxiv.org/abs/2310.0025

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

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Nov 9, 2023

Jun 22, 2024 11:06 AM

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

EntGPT: Linking Generative Large Language Models with Knowledge Bases

Prompt Design and Engineering: Introduction and Advanced Methods

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

https://arxiv.org/abs/2311.052

Chain-of-Verification Reduces Hallucination in Large Language Models

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Sep 20, 2023

Jun 22, 2024 11:06 AM

One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era

Reasoning with Language Model Prompting: A Survey

Towards Reasoning in Large Language Models: A Survey

https://arxiv.org/abs/2309.11495

Boosted Prompt Ensembles for Large Language Models

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Apr 12, 2023

Jun 22, 2024 11:03 AM

Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling

Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency

SatLM: Satisfiability-Aided Language Models Using Declarative Prompting

REFINER: Reasoning Feedback on Intermediate Representations

Reflexion: Language Agents with Verbal Reinforcement Learning

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

Self-Refine: Iterative Refinement with Self-Feedback

Fairness-guided Few-shot Prompting for Large Language Models

Context-faithful Prompting for Large Language Models

Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer

CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification

Larger language models do in-context learning differently

OpenICL: An Open-Source Framework for In-context Learning

Dynamic Prompting: A Unified Framework for Prompt Tuning

https://arxiv.org/abs/2304.05970

Reflexion: Language Agents with Verbal Reinforcement Learning

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Jun 20, 2024 01:42 PM

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

https://arxiv.org/pdf/2303.11366.pdf

Prompt Injection: Different Attacks and Defensive Techniques

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May 9, 2024

Featured

Jun 20, 2024 01:41 PM

Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models

Universal and Transferable Adversarial Attacks on Aligned Language Models

Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification

From Noise to Clarity: Unraveling the Adversarial Suffix of Large Language Model Attacks via Translation of Text Embeddings

Mistral 7B: Foundation Model Research Paper Summary

WizardLM: Empowering Large Language Models to Follow Complex Instructions

EntGPT: Linking Generative Large Language Models with Knowledge Bases

CYBERSECEVAL 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models

Language Prompt for Autonomous Driving

EntGPT: Linking Generative Large Language Models with Knowledge Bases

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Feb 9, 2024

Jun 20, 2024 01:40 PM

From Noise to Clarity: Unraveling the Adversarial Suffix of Large Language Model Attacks via Translation of Text Embeddings

Universal and Transferable Adversarial Attacks on Aligned Language Models

Prompt Injection: Different Attacks and Defensive Techniques

Factuality of Large Language Models in the Year 2024

KnowGPT: Knowledge Injection for Large Language Models

Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

https://arxiv.org/abs/2402.06738

Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning

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Nov 13, 2023

Jun 20, 2024 01:40 PM

Many-Shot Jailbreaking (Anthropic Research)

Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources

Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

AutoHall: Automated Hallucination Dataset Generation for Large Language Models

https://arxiv.org/abs/2311.08505

Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources

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May 22, 2023

Jun 20, 2024 01:39 PM

Factuality of Large Language Models in the Year 2024

Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources

Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning

Fine-tuning Language Models for Factuality

https://arxiv.org/abs/2305.13269

Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks

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Apr 28, 2023

Jun 20, 2024 01:39 PM

WizardLM: Empowering Large Language Models to Follow Complex Instructions

Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification

Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions

AutoHall: Automated Hallucination Dataset Generation for Large Language Models

https://arxiv.org/abs/2304.14732

Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions

Ready to Publish

Nov 23, 2023

Jun 20, 2024 01:39 PM

Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks

EntGPT: Linking Generative Large Language Models with Knowledge Bases

AutoHall: Automated Hallucination Dataset Generation for Large Language Models

A Step Closer to Comprehensive Answers: Constrained Multi-Stage Question Decomposition with Large Language Models

Prompt Design and Engineering: Introduction and Advanced Methods

https://arxiv.org/abs/2311.13982

Prompt Design and Engineering: Introduction and Advanced Methods

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Jan 24, 2024

Jun 20, 2024 01:39 PM

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Re-Reading Improves Reasoning in Large Language Models

Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting

Post Hoc Explanations of Language Models Can Improve Language Models

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Model-tuning Via Prompts Makes NLP Models Adversarially Robust

Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction Following

Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data

Global Prompt Cell: A Portable Control Module for Effective Prompt Tuning

https://arxiv.org/abs/2401.14423

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Ready to Publish

Sep 23, 2023

Jun 20, 2024 01:38 PM

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

A Step Closer to Comprehensive Answers: Constrained Multi-Stage Question Decomposition with Large Language Models

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting

Model-tuning Via Prompts Makes NLP Models Adversarially Robust

Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction Following

Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data

https://arxiv.org/abs/2309.13339

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

Ready to Publish

Dec 26, 2023

Jun 20, 2024 01:38 PM

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

A Step Closer to Comprehensive Answers: Constrained Multi-Stage Question Decomposition with Large Language Models

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Re-Reading Improves Reasoning in Large Language Models

https://arxiv.org/abs/2312.16171v1

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Ready to Publish

Oct 3, 2023

Jun 20, 2024 01:38 PM

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Prompt Design and Engineering: Introduction and Advanced Methods

https://arxiv.org/abs/2310.01714

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Ready to Publish

Oct 9, 2023

Jun 20, 2024 01:38 PM

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Prompt Design and Engineering: Introduction and Advanced Methods

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Re-Reading Improves Reasoning in Large Language Models

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Model-tuning Via Prompts Makes NLP Models Adversarially Robust

Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction Following

https://arxiv.org/abs/2310.05736

Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Ready to Publish

Sep 15, 2023

Jun 20, 2024 01:37 PM

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data

https://arxiv.org/abs/2309.08532

Re-Reading Improves Reasoning in Large Language Models

Ready to Publish

Sep 12, 2023

Jun 20, 2024 01:36 PM

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

Prompt Design and Engineering: Introduction and Advanced Methods

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

Post Hoc Explanations of Language Models Can Improve Language Models

https://arxiv.org/abs/2309.06275

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

Ready to Publish

Jul 28, 2023

Jun 20, 2024 01:36 PM

Re-Reading Improves Reasoning in Large Language Models

Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Post Hoc Explanations of Language Models Can Improve Language Models

https://arxiv.org/abs/2307.15337

Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting

Ready to Publish

May 23, 2023

Jun 20, 2024 01:36 PM

Prompt Design and Engineering: Introduction and Advanced Methods

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models

https://arxiv.org/abs/2305.13733

Post Hoc Explanations of Language Models Can Improve Language Models

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May 19, 2023

Jun 20, 2024 01:33 PM

Re-Reading Improves Reasoning in Large Language Models

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

Prompt Design and Engineering: Introduction and Advanced Methods

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models

https://arxiv.org/abs/2305.11426

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Ready to Publish

May 17, 2023

Jun 20, 2024 01:33 PM

Prompt Design and Engineering: Introduction and Advanced Methods

Post Hoc Explanations of Language Models Can Improve Language Models

Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting

Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models

https://arxiv.org/abs/2305.10601

Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models

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May 17, 2023

Jun 20, 2024 01:33 PM

Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting

Post Hoc Explanations of Language Models Can Improve Language Models

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

https://arxiv.org/abs/2305.09955

A Comprehensive Survey on Instruction Following

Ready to Publish

Mar 18, 2023

Jun 20, 2024 01:32 PM

A Step Closer to Comprehensive Answers: Constrained Multi-Stage Question Decomposition with Large Language Models

Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Global Prompt Cell: A Portable Control Module for Effective Prompt Tuning

Revisiting Automated Prompting: Are We Actually Doing Better?

NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference

Visual-Language Prompt Tuning with Knowledge-guided Context Optimization

Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data

https://arxiv.org/abs/2303.10475

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Ready to Publish

Mar 15, 2023

Jun 20, 2024 01:32 PM

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Prompt Design and Engineering: Introduction and Advanced Methods

Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models

https://arxiv.org/abs/2303.08518

Model-tuning Via Prompts Makes NLP Models Adversarially Robust

Ready to Publish

Mar 13, 2023

Jun 20, 2024 01:31 PM

Prompt Design and Engineering: Introduction and Advanced Methods

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Exploring LLM-based Agents for Root Cause Analysis

Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond

https://arxiv.org/abs/2303.07320

Investigating the Effectiveness of Task-Agnostic Prefix Prompt for Instruction Following

Ready to Publish

Feb 28, 2023

Jun 20, 2024 01:31 PM

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

Prompt Design and Engineering: Introduction and Advanced Methods

Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond

https://arxiv.org/abs/2302.14691

Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data

Ready to Publish

Feb 24, 2023

Jun 20, 2024 01:31 PM

Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic

Prompt Design and Engineering: Introduction and Advanced Methods

Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Exploring LLM-based Agents for Root Cause Analysis

Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

https://arxiv.org/abs/2302.12822

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

Ready to Publish

May 23, 2023

Jun 20, 2024 01:24 PM

Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

Exploring LLM-based Agents for Root Cause Analysis

A Bibliometric Review of Large Language Models Research from 2017 to 2023

From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

Hierarchical Prompting Assists Large Language Model on Web Navigation

Interactive Natural Language Processing

https://arxiv.org/abs/2305.13860

A Taxonomy of Prompt Modifiers for Text-To-Image Generation

Ready to Publish

Apr 20, 2022

Jun 20, 2024 01:24 PM

Towards Reasoning in Large Language Models: A Survey

Reasoning with Language Model Prompting: A Survey

Emergent Abilities of Large Language Models

https://arxiv.org/abs/2204.13988

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

Ready to Publish

Jul 28, 2021

Jun 20, 2024 01:24 PM

Towards Reasoning in Large Language Models: A Survey

Augmented Language Models: a Survey

https://arxiv.org/abs/2107.13586

From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

Ready to Publish

Sep 8, 2023

Jun 20, 2024 01:23 PM

Towards Reasoning in Large Language Models: A Survey

Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

https://arxiv.org/abs/2309.04269

Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Ready to Publish

Aug 18, 2023

Jun 20, 2024 01:23 PM

Reasoning with Language Model Prompting: A Survey

Towards Reasoning in Large Language Models: A Survey

Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Less Likely Brainstorming: Using Language Models to Generate Alternative Hypotheses

Universality and Limitations of Prompt Tuning

MultiTool-CoT: GPT-3 Can Use Multiple External Tools with Chain of Thought Prompting

Reasoning with Language Model is Planning with World Model

Better Zero-Shot Reasoning with Self-Adaptive Prompting

Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs

TreePrompt: Learning to Compose Tree Prompts for Explainable Visual Grounding

https://arxiv.org/abs/2308.09687v2

Exploring Lottery Prompts for Pre-trained Language Models

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May 31, 2023

Jun 20, 2024 01:22 PM

Towards Reasoning in Large Language Models: A Survey

Reasoning with Language Model Prompting: A Survey

Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond

https://arxiv.org/abs/2305.19500

PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents

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May 23, 2023

Jun 20, 2024 01:22 PM

Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond

A Bibliometric Review of Large Language Models Research from 2017 to 2023

Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

https://arxiv.org/abs/2305.14564v1

Better Zero-Shot Reasoning with Self-Adaptive Prompting

Ready to Publish

May 23, 2023

Jun 20, 2024 01:22 PM

Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond

Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

https://arxiv.org/abs/2305.14106

Hierarchical Prompting Assists Large Language Model on Web Navigation

Ready to Publish

May 23, 2023

Jun 20, 2024 01:21 PM

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

A Bibliometric Review of Large Language Models Research from 2017 to 2023

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

https://arxiv.org/abs/2305.14257

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

Ready to Publish

Mar 31, 2023

Jun 20, 2024 01:12 PM

Boosted Prompt Ensembles for Large Language Models

Global Prompt Cell: A Portable Control Module for Effective Prompt Tuning

Why think step by step? Reasoning emerges from the locality of experience

https://arxiv.org/abs/2303.17760

Dynamic Prompting: A Unified Framework for Prompt Tuning

Ready to Publish

Mar 6, 2023

Jun 20, 2024 01:12 PM

Boosted Prompt Ensembles for Large Language Models

Revisiting Automated Prompting: Are We Actually Doing Better?

CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification

ART: Automatic multi-step reasoning and tool-use for large language models

Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

https://arxiv.org/abs/2303.02909

EvoPrompting: Language Models for Code-Level Neural Architecture Search

Ready to Publish

Feb 28, 2023

Jun 20, 2024 01:11 PM

How Robust is GPT-3.5 to Predecessors? A Comprehensive Study on Language Understanding Tasks

Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners

Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data

Active Prompting with Chain-of-Thought for Large Language Models

Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection

https://arxiv.org/abs/2302.14838

A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

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Feb 21, 2023

Jun 20, 2024 01:11 PM

Language Is Not All You Need: Aligning Perception with Language Models

Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection

Active Prompting with Chain-of-Thought for Large Language Models

Guiding Large Language Models via Directional Stimulus Prompting

How Does In-Context Learning Help Prompt Tuning?

A-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting

https://arxiv.org/abs/2302.11382

Guiding Large Language Models via Directional Stimulus Prompting

Ready to Publish

Oct 9, 2023

Jun 20, 2024 01:11 PM

A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

Language Is Not All You Need: Aligning Perception with Language Models

Active Prompting with Chain-of-Thought for Large Language Models

How Does In-Context Learning Help Prompt Tuning?

https://arxiv.org/abs/2302.11520

Scalable Prompt Generation for Semi-supervised Learning with Language Models

Ready to Publish

Feb 18, 2023

Jun 20, 2024 01:10 PM

How Does In-Context Learning Help Prompt Tuning?

Chain of Hindsight Aligns Language Models with Feedback

Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data

The Capacity for Moral Self-Correction in Large Language Models

https://arxiv.org/abs/2302.09236

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Ready to Publish

Feb 25, 2023

Jun 20, 2024 01:06 PM

Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints

A-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting

How Does In-Context Learning Help Prompt Tuning?

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Progressive Prompts: Continual Learning for Language Models

Batch Prompting: Efficient Inference with Large Language Model APIs

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning

Constitutional AI: Harmlessness from AI Feedback

Large Language Models are reasoners with Self-Verification

https://arxiv.org/abs/2302.08043

The Capacity for Moral Self-Correction in Large Language Models

Ready to Publish

Feb 18, 2023

Jun 20, 2024 01:04 PM

Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints

Scalable Prompt Generation for Semi-supervised Learning with Language Models

How Does In-Context Learning Help Prompt Tuning?

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

Compositional Exemplars for In-context Learning

https://arxiv.org/abs/2302.07459

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

Ready to Publish

Feb 14, 2023

Jun 20, 2024 01:04 PM

The Capacity for Moral Self-Correction in Large Language Models

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

A-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting

Compositional Exemplars for In-context Learning

Multimodal Chain-of-Thought Reasoning in Language Models

Large Language Models Can Be Easily Distracted by Irrelevant Context

Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models

https://arxiv.org/abs/2302.06868

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Ready to Publish

Feb 11, 2023

Jun 20, 2024 01:04 PM

The Capacity for Moral Self-Correction in Large Language Models

Compositional Exemplars for In-context Learning

Multimodal Chain-of-Thought Reasoning in Language Models

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

https://arxiv.org/abs/2302.05619

Compositional Exemplars for In-context Learning

Ready to Publish

Jun 20, 2023

Jun 20, 2024 01:03 PM

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

The Capacity for Moral Self-Correction in Large Language Models

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Multimodal Chain-of-Thought Reasoning in Language Models

Retrieval-Augmented Thought Process as Sequential Decision Making

https://arxiv.org/abs/2302.05698

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Ready to Publish

Jun 1, 2023

Jun 20, 2024 12:55 PM

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Compositional Exemplars for In-context Learning

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Large Language Models Can Be Easily Distracted by Irrelevant Context

Batch Prompting: Efficient Inference with Large Language Model APIs

On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning

https://arxiv.org/abs/2302.03668

Multimodal Chain-of-Thought Reasoning in Language Models

Ready to Publish

Feb 17, 2023

Jun 20, 2024 12:54 PM

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

Compositional Exemplars for In-context Learning

Large Language Models Can Be Easily Distracted by Irrelevant Context

Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models

Progressive Prompts: Continual Learning for Language Models

Batch Prompting: Efficient Inference with Large Language Model APIs

Retrieval-Augmented Thought Process as Sequential Decision Making

https://arxiv.org/abs/2302.00923

Large Language Models Can Be Easily Distracted by Irrelevant Context

Ready to Publish

Jun 6, 2023

Jun 20, 2024 12:54 PM

Multimodal Chain-of-Thought Reasoning in Language Models

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models

Progressive Prompts: Continual Learning for Language Models

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

https://arxiv.org/abs/2302.00093

Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models

Ready to Publish

Feb 1, 2023

Jun 20, 2024 12:54 PM

SwitchPrompt: Learning Domain-Specific Gated Soft Prompts for Classification in Low-Resource Domains

Multimodal Chain-of-Thought Reasoning in Language Models

Large Language Models Can Be Easily Distracted by Irrelevant Context

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

https://arxiv.org/abs/2302.00618

Progressive Prompts: Continual Learning for Language Models

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Jan 29, 2023

Jun 20, 2024 12:54 PM

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Multimodal Chain-of-Thought Reasoning in Language Models

Large Language Models Can Be Easily Distracted by Irrelevant Context

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

https://arxiv.org/abs/2301.12314

Batch Prompting: Efficient Inference with Large Language Model APIs

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Oct 24, 2023

Jun 20, 2024 12:53 PM

Multimodal Chain-of-Thought Reasoning in Language Models

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Constitutional AI: Harmlessness from AI Feedback

Successive Prompting for Decomposing Complex Questions

https://arxiv.org/abs/2301.08721

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

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Jan 23, 2023

Jun 20, 2024 12:53 PM

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Large Language Models Can Be Easily Distracted by Irrelevant Context

Successive Prompting for Decomposing Complex Questions

Large Language Models are reasoners with Self-Verification

https://arxiv.org/abs/2212.14024

On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning

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Jun 4, 2023

Jun 20, 2024 12:53 PM

Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery

Large Language Models Can Be Easily Distracted by Irrelevant Context

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Constitutional AI: Harmlessness from AI Feedback

https://arxiv.org/abs/2212.08061

Constitutional AI: Harmlessness from AI Feedback

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Dec 15, 2022

Jun 20, 2024 12:52 PM

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning

Batch Prompting: Efficient Inference with Large Language Model APIs

Successive Prompting for Decomposing Complex Questions

Large Language Models are reasoners with Self-Verification

Demystifying Chains, Trees, and Graphs of Thoughts

https://arxiv.org/abs/2212.08073

Successive Prompting for Decomposing Complex Questions

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Dec 8, 2022

Jun 20, 2024 12:51 PM

Batch Prompting: Efficient Inference with Large Language Model APIs

Constitutional AI: Harmlessness from AI Feedback

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

https://arxiv.org/abs/2212.04092

Large Language Models are reasoners with Self-Verification

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Dec 19, 2022

Jun 20, 2024 12:51 PM

Constitutional AI: Harmlessness from AI Feedback

GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Demystifying Chains, Trees, and Graphs of Thoughts

https://arxiv.org/abs/2212.09561v1

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

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Feb 14, 2023

Jun 20, 2024 12:51 PM

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Successive Prompting for Decomposing Complex Questions

Progressive Prompts: Continual Learning for Language Models

Demystifying Chains, Trees, and Graphs of Thoughts

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

https://arxiv.org/abs/2301.13688

Demystifying Chains, Trees, and Graphs of Thoughts

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Apr 5, 2024

Jun 20, 2024 12:50 PM

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Large Language Models are reasoners with Self-Verification

Constitutional AI: Harmlessness from AI Feedback

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

https://arxiv.org/abs/2401.14295

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

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Oct 27, 2023

Jun 20, 2024 12:50 PM

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Large Language Models Can Be Easily Distracted by Irrelevant Context

Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Empowering Multi-step Reasoning across Languages via Tree-of-Thoughts

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

GuReT: Distinguishing Guilt and Regret related Text

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models

PathFinder: Guided Search over Multi-Step Reasoning Paths

SPROUT: Authoring Programming Tutorials with Interactive Visualization of Large Language Model Generation Process

NLPBench: Evaluating Large Language Models on Solving NLP Problems

Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering

https://arxiv.org/pdf/2310.14735

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

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Sep 28, 2023

Jun 20, 2024 12:50 PM

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Demystifying Chains, Trees, and Graphs of Thoughts

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning

https://arxiv.org/abs/2308.10379

Retrieval-Augmented Thought Process as Sequential Decision Making

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Feb 12, 2024

Jun 20, 2024 12:49 PM

Retrieval-Augmented Thought Process as Sequential Decision Making

Multimodal Chain-of-Thought Reasoning in Language Models

Compositional Exemplars for In-context Learning

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

https://arxiv.org/abs/2402.07812

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

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Feb 23, 2024

Jun 20, 2024 12:49 PM

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Retrieval-Augmented Thought Process as Sequential Decision Making

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Empowering Multi-step Reasoning across Languages via Tree-of-Thoughts

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning

MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems

https://arxiv.org/abs/2311.04254

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

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Feb 9, 2024

Jun 20, 2024 12:49 PM

Dynamic Prompting: A Unified Framework for Prompt Tuning

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Larger language models do in-context learning differently

Empowering Multi-step Reasoning across Languages via Tree-of-Thoughts

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning

MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems

https://arxiv.org/abs/2309.17179

Empowering Multi-step Reasoning across Languages via Tree-of-Thoughts

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Apr 19, 2024

Jun 20, 2024 12:48 PM

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

https://arxiv.org/abs/2311.08097

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

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Aug 16, 2023

Jun 20, 2024 12:48 PM

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Retrieval-Augmented Thought Process as Sequential Decision Making

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Founder-GPT: Self-play to evaluate the Founder-Idea fit

https://arxiv.org/abs/2308.08614

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

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Feb 21, 2024

Jun 20, 2024 12:48 PM

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Retrieval-Augmented Thought Process as Sequential Decision Making

https://arxiv.org/abs/2312.02119

Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning

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Aug 21, 2023

Jun 20, 2024 12:48 PM

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems

GuReT: Distinguishing Guilt and Regret related Text

https://arxiv.org/abs/2308.09658

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

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May 15, 2023

Jun 20, 2024 12:47 PM

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning

Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

GuReT: Distinguishing Guilt and Regret related Text

Founder-GPT: Self-play to evaluate the Founder-Idea fit

https://arxiv.org/abs/2305.08291

MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems

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Apr 6, 2024

Jun 20, 2024 12:47 PM

Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation

Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning

Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

https://arxiv.org/abs/2404.04735

Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

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Feb 12, 2024

Jun 20, 2024 12:47 PM

MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering

Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines

https://arxiv.org/abs/2402.07408

GuReT: Distinguishing Guilt and Regret related Text

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Jan 29, 2024

Jun 20, 2024 12:46 PM

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning

Founder-GPT: Self-play to evaluate the Founder-Idea fit

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models

AI Chain on Large Language Model for Unsupervised Control Flow Graph Generation for Statically-Typed Partial Code

PathFinder: Guided Search over Multi-Step Reasoning Paths

SPROUT: Authoring Programming Tutorials with Interactive Visualization of Large Language Model Generation Process

NLPBench: Evaluating Large Language Models on Solving NLP Problems

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation

Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering

Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering

Chain-of-Thought Reasoning is a Policy Improvement Operator

Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

https://arxiv.org/abs/2401.16541

Founder-GPT: Self-play to evaluate the Founder-Idea fit

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Dec 20, 2023

Jun 20, 2024 12:45 PM

GuReT: Distinguishing Guilt and Regret related Text

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models

AI Chain on Large Language Model for Unsupervised Control Flow Graph Generation for Statically-Typed Partial Code

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation

Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering

Autonomous Tree-search Ability of Large Language Models

LLM Guided Evolution -- The Automation of Models Advancing Models

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

On the Empirical Complexity of Reasoning and Planning in LLMs

STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent

RoT: Enhancing Large Language Models with Reflection on Search Trees

DiffusionGPT: LLM-Driven Text-to-Image Generation System

https://arxiv.org/abs/2312.12037

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

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May 10, 2024

Jun 20, 2024 12:44 PM

Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

GuReT: Distinguishing Guilt and Regret related Text

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Chain-of-Thought Reasoning is a Policy Improvement Operator

LLM Guided Evolution -- The Automation of Models Advancing Models

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations

Analyzing Toxicity in Deep Conversations: A Reddit Case Study

RoT: Enhancing Large Language Models with Reflection on Search Trees

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

Text2MDT: Extracting Medical Decision Trees from Medical Texts

https://arxiv.org/abs/2402.18510

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models

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Feb 17, 2024

Jun 20, 2024 12:44 PM

GuReT: Distinguishing Guilt and Regret related Text

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Founder-GPT: Self-play to evaluate the Founder-Idea fit

AI Chain on Large Language Model for Unsupervised Control Flow Graph Generation for Statically-Typed Partial Code

PathFinder: Guided Search over Multi-Step Reasoning Paths

https://arxiv.org/abs/2402.11140

AI Chain on Large Language Model for Unsupervised Control Flow Graph Generation for Statically-Typed Partial Code

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Jun 1, 2023

Jun 20, 2024 12:44 PM

GuReT: Distinguishing Guilt and Regret related Text

Founder-GPT: Self-play to evaluate the Founder-Idea fit

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models

https://arxiv.org/abs/2306.00757

PathFinder: Guided Search over Multi-Step Reasoning Paths

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Dec 12, 2023

Jun 20, 2024 12:43 PM

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

GuReT: Distinguishing Guilt and Regret related Text

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models

SPROUT: Authoring Programming Tutorials with Interactive Visualization of Large Language Model Generation Process

NLPBench: Evaluating Large Language Models on Solving NLP Problems

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation

Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering

Autonomous Tree-search Ability of Large Language Models

Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

On the Empirical Complexity of Reasoning and Planning in LLMs

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations

Analyzing Toxicity in Deep Conversations: A Reddit Case Study

RoT: Enhancing Large Language Models with Reflection on Search Trees

LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

Text2MDT: Extracting Medical Decision Trees from Medical Texts

https://arxiv.org/abs/2312.05180

SPROUT: Authoring Programming Tutorials with Interactive Visualization of Large Language Model Generation Process

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Dec 4, 2023

Jun 20, 2024 12:43 PM

GuReT: Distinguishing Guilt and Regret related Text

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

PathFinder: Guided Search over Multi-Step Reasoning Paths

Autonomous Tree-search Ability of Large Language Models

https://arxiv.org/abs/2312.01801

NLPBench: Evaluating Large Language Models on Solving NLP Problems

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Oct 19, 2023

Jun 20, 2024 12:42 PM

GuReT: Distinguishing Guilt and Regret related Text

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

PathFinder: Guided Search over Multi-Step Reasoning Paths

https://arxiv.org/abs/2309.15630

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation

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Mar 1, 2024

Jun 20, 2024 12:42 PM

PathFinder: Guided Search over Multi-Step Reasoning Paths

GuReT: Distinguishing Guilt and Regret related Text

Founder-GPT: Self-play to evaluate the Founder-Idea fit

https://arxiv.org/abs/2310.02304

Knowledge-Driven CoT: Exploring Faithful Reasoning in LLMs for Knowledge-intensive Question Answering

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Oct 28, 2023

Jun 20, 2024 12:42 PM

PathFinder: Guided Search over Multi-Step Reasoning Paths

GuReT: Distinguishing Guilt and Regret related Text

Founder-GPT: Self-play to evaluate the Founder-Idea fit

https://arxiv.org/abs/2308.13259

Autonomous Tree-search Ability of Large Language Models

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Oct 14, 2023

Jun 20, 2024 12:42 PM

PathFinder: Guided Search over Multi-Step Reasoning Paths

SPROUT: Authoring Programming Tutorials with Interactive Visualization of Large Language Model Generation Process

Founder-GPT: Self-play to evaluate the Founder-Idea fit

https://arxiv.org/abs/2310.10686

Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering

Ready to Publish

Apr 22, 2024

Jun 20, 2024 12:41 PM

Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

GuReT: Distinguishing Guilt and Regret related Text

Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

Chain-of-Thought Reasoning is a Policy Improvement Operator

LLM Guided Evolution -- The Automation of Models Advancing Models

https://arxiv.org/abs/2404.14464

Chain-of-Thought Reasoning is a Policy Improvement Operator

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Nov 8, 2023

Jun 20, 2024 12:41 PM

Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering

GuReT: Distinguishing Guilt and Regret related Text

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

https://arxiv.org/abs/2309.08589

LLM Guided Evolution -- The Automation of Models Advancing Models

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Mar 18, 2024

Jun 20, 2024 12:41 PM

Founder-GPT: Self-play to evaluate the Founder-Idea fit

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Tree of Reviews: A Tree-based Dynamic Iterative Retrieval Framework for Multi-hop Question Answering

https://arxiv.org/abs/2403.11446

Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines

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Jan 23, 2024

Jun 20, 2024 12:41 PM

GuReT: Distinguishing Guilt and Regret related Text

PathFinder: Guided Search over Multi-Step Reasoning Paths

Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples

https://arxiv.org/abs/2401.11120

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

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Apr 18, 2024

Jun 20, 2024 12:40 PM

Founder-GPT: Self-play to evaluate the Founder-Idea fit

GuReT: Distinguishing Guilt and Regret related Text

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent

LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding

DiffusionGPT: LLM-Driven Text-to-Image Generation System

Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences

ResearDesign Guidelines for Prompt Engineering Text-to-Image Generative Models

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Self-Consistency Improves Chain of Thought Reasoning in Language Models

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

https://arxiv.org/abs/2404.12065

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

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Jan 11, 2024

Jun 20, 2024 12:40 PM

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

PathFinder: Guided Search over Multi-Step Reasoning Paths

On the Empirical Complexity of Reasoning and Planning in LLMs

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations

Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent

Analyzing Toxicity in Deep Conversations: A Reddit Case Study

LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding

DiffusionGPT: LLM-Driven Text-to-Image Generation System

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

Text2MDT: Extracting Medical Decision Trees from Medical Texts

Automatic Root Cause Analysis via Large Language Models for Cloud Incidents

https://arxiv.org/abs/2401.05787

On the Empirical Complexity of Reasoning and Planning in LLMs

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Apr 17, 2024

Jun 20, 2024 12:40 PM

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

PathFinder: Guided Search over Multi-Step Reasoning Paths

Founder-GPT: Self-play to evaluate the Founder-Idea fit

https://arxiv.org/abs/2404.11041

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations

Ready to Publish

Feb 19, 2024

Jun 20, 2024 12:40 PM

PathFinder: Guided Search over Multi-Step Reasoning Paths

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

https://arxiv.org/abs/2402.12348

Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

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Jun 19, 2023

Jun 20, 2024 12:39 PM

GuReT: Distinguishing Guilt and Regret related Text

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

https://arxiv.org/abs/2306.11025

STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent

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Jan 7, 2024

Jun 20, 2024 12:39 PM

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Founder-GPT: Self-play to evaluate the Founder-Idea fit

https://arxiv.org/abs/2310.01775

Analyzing Toxicity in Deep Conversations: A Reddit Case Study

Ready to Publish

Apr 11, 2024

Jun 20, 2024 12:39 PM

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

PathFinder: Guided Search over Multi-Step Reasoning Paths

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

https://arxiv.org/abs/2404.07879

RoT: Enhancing Large Language Models with Reflection on Search Trees

Ready to Publish

Apr 11, 2024

Jun 20, 2024 12:39 PM

PathFinder: Guided Search over Multi-Step Reasoning Paths

Founder-GPT: Self-play to evaluate the Founder-Idea fit

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

https://arxiv.org/abs/2404.05449

GuReT: Distinguishing Guilt and Regret related Text

Ready to Publish

Mar 2, 2024

Jun 20, 2024 12:38 PM

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

PathFinder: Guided Search over Multi-Step Reasoning Paths

Self-Consistency Improves Chain of Thought Reasoning in Language Models

https://arxiv.org/abs/2401.03790

LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding

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Apr 8, 2024

Jun 20, 2024 12:38 PM

PathFinder: Guided Search over Multi-Step Reasoning Paths

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

https://arxiv.org/abs/2404.05225

DiffusionGPT: LLM-Driven Text-to-Image Generation System

Ready to Publish

Jan 18, 2024

Jun 20, 2024 12:38 PM

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

Founder-GPT: Self-play to evaluate the Founder-Idea fit

ResearDesign Guidelines for Prompt Engineering Text-to-Image Generative Models

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Making Large Language Models Better Reasoners with Step-Aware Verifier

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

https://arxiv.org/abs/2401.10061

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

Ready to Publish

Dec 7, 2023

Jun 20, 2024 12:37 PM

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

PathFinder: Guided Search over Multi-Step Reasoning Paths

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Automatic Root Cause Analysis via Large Language Models for Cloud Incidents

Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences

ResearDesign Guidelines for Prompt Engineering Text-to-Image Generative Models

Self-Consistency Improves Chain of Thought Reasoning in Language Models

Making Large Language Models Better Reasoners with Step-Aware Verifier

https://arxiv.org/abs/2310.16427

Text2MDT: Extracting Medical Decision Trees from Medical Texts

Ready to Publish

Jan 4, 2024

Jun 20, 2024 12:37 PM

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

PathFinder: Guided Search over Multi-Step Reasoning Paths

RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval

Automatic Root Cause Analysis via Large Language Models for Cloud Incidents

Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Making Large Language Models Better Reasoners with Step-Aware Verifier

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

https://arxiv.org/abs/2401.02034

Automatic Root Cause Analysis via Large Language Models for Cloud Incidents

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Nov 13, 2023

Jun 20, 2024 12:37 PM

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning

Text2MDT: Extracting Medical Decision Trees from Medical Texts

https://arxiv.org/abs/2305.15778

Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences

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Apr 18, 2024

Jun 20, 2024 12:37 PM

Text2MDT: Extracting Medical Decision Trees from Medical Texts

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

https://arxiv.org/abs/2404.12272

ResearDesign Guidelines for Prompt Engineering Text-to-Image Generative Models

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Sep 28, 2023

Jun 20, 2024 12:23 PM

DiffusionGPT: LLM-Driven Text-to-Image Generation System

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

https://arxiv.org/abs/2109.06977

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

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Jan 10, 2023

Jun 20, 2024 12:23 PM

Text2MDT: Extracting Medical Decision Trees from Medical Texts

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

DiffusionGPT: LLM-Driven Text-to-Image Generation System

https://arxiv.org/abs/2201.11903

Self-Consistency Improves Chain of Thought Reasoning in Language Models

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Mar 7, 2023

Jun 20, 2024 12:23 PM

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

https://arxiv.org/abs/2203.11171

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

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Jan 29, 2023

Jun 20, 2024 12:22 PM

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding

https://arxiv.org/abs/2205.11916

Making Large Language Models Better Reasoners with Step-Aware Verifier

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May 24, 2023

Jun 20, 2024 12:22 PM

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

Text2MDT: Extracting Medical Decision Trees from Medical Texts

DiffusionGPT: LLM-Driven Text-to-Image Generation System

DocPrompting: Generating Code by Retrieving the Docs

https://arxiv.org/abs/2206.02336

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

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Mar 2, 2023

Jun 20, 2024 12:22 PM

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models

Text2MDT: Extracting Medical Decision Trees from Medical Texts

DiffusionGPT: LLM-Driven Text-to-Image Generation System

DocPrompting: Generating Code by Retrieving the Docs

Large Language Models Are Human-Level Prompt Engineers

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

https://arxiv.org/abs/2209.14610

DocPrompting: Generating Code by Retrieving the Docs

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Feb 18, 2023

Jun 20, 2024 12:21 PM

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

DocPrompting: Generating Code by Retrieving the Docs

Making Large Language Models Better Reasoners with Step-Aware Verifier

Large Language Models Are Human-Level Prompt Engineers

Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

Prompt Engineering for Healthcare: Methodologies and Applications

Prompt Engineering or Fine Tuning: An Empirical Assessment of Large Language Models in Automated Software Engineering Tasks

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

Understanding prompt engineering may not require rethinking generalization

To be or not to be? an exploration of continuously controllable prompt engineering

PEACE: Prompt Engineering Automation for CLIPSeg Enhancement in Aerial Robotics

Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues

Prompt-Engineering and Transformer-based Question Generation and Evaluation

Prompt Engineering-assisted Malware Dynamic Analysis Using GPT-4

Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

https://arxiv.org/abs/2207.05987

Making Large Language Models Better Reasoners with Step-Aware Verifier

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Jan 27, 2023

Jun 20, 2024 12:21 PM

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

Self-Consistency Improves Chain of Thought Reasoning in Language Models

Large Language Models Are Human-Level Prompt Engineers

Decomposed Prompting: A Modular Approach for Solving Complex Tasks

Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

PEACE: Prompt Engineering Automation for CLIPSeg Enhancement in Aerial Robotics

Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues

Prompt Engineering-assisted Malware Dynamic Analysis Using GPT-4

Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies

https://arxiv.org/abs/2211.10435

Large Language Models Are Human-Level Prompt Engineers

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Mar 10, 2023

Jun 20, 2024 12:20 PM

DocPrompting: Generating Code by Retrieving the Docs

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

ReAct: Synergizing Reasoning and Acting in Language Models

Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

Prompt Engineering or Fine Tuning: An Empirical Assessment of Large Language Models in Automated Software Engineering Tasks

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering

Prompt Engineering-assisted Malware Dynamic Analysis Using GPT-4

https://arxiv.org/abs/2211.01910

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

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May 8, 2023

Jun 20, 2024 12:20 PM

Large Language Models Are Human-Level Prompt Engineers

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning

ReAct: Synergizing Reasoning and Acting in Language Models

Decomposed Prompting: A Modular Approach for Solving Complex Tasks

Prompt Engineering for Healthcare: Methodologies and Applications

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

PEACE: Prompt Engineering Automation for CLIPSeg Enhancement in Aerial Robotics

https://arxiv.org/abs/2210.07321

DocPrompting: Generating Code by Retrieving the Docs

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Feb 16, 2023

Jun 20, 2024 12:20 PM

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

https://arxiv.org/abs/2210.01296

ReAct: Synergizing Reasoning and Acting in Language Models

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Mar 10, 2023

Jun 20, 2024 12:19 PM

Large Language Models Are Human-Level Prompt Engineers

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

ReAct: Synergizing Reasoning and Acting in Language Models

Prompt Engineering for Healthcare: Methodologies and Applications

Understanding prompt engineering may not require rethinking generalization

Prompt-Engineering and Transformer-based Question Generation and Evaluation

Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT

https://arxiv.org/abs/2210.03629

DocPrompting: Generating Code by Retrieving the Docs

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Feb 15, 2023

Jun 20, 2024 12:19 PM

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Decomposed Prompting: A Modular Approach for Solving Complex Tasks

Prompt Engineering or Fine Tuning: An Empirical Assessment of Large Language Models in Automated Software Engineering Tasks

Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering

Understanding prompt engineering may not require rethinking generalization

To be or not to be? an exploration of continuously controllable prompt engineering

Prompt-Engineering and Transformer-based Question Generation and Evaluation

Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT

Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

https://arxiv.org/abs/2210.09150

Decomposed Prompting: A Modular Approach for Solving Complex Tasks

Ready to Publish

Apr 11, 2023

Jun 20, 2024 12:19 PM

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

https://arxiv.org/abs/2210.02406

Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

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Jan 26, 2023

Featured

Jun 20, 2024 12:18 PM

DocPrompting: Generating Code by Retrieving the Docs

Large Language Models Are Human-Level Prompt Engineers

https://arxiv.org/abs/2210.01240v3

Prompt Engineering for Healthcare: Methodologies and Applications

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Mar 23, 2024

Jun 20, 2024 12:17 PM

ReAct: Synergizing Reasoning and Acting in Language Models

DocPrompting: Generating Code by Retrieving the Docs

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

https://arxiv.org/abs/2304.14670

DocPrompting: Generating Code by Retrieving the Docs

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Feb 19, 2024

Jun 20, 2024 12:17 PM

Large Language Models Are Human-Level Prompt Engineers

https://arxiv.org/abs/2311.05661

Prompt Engineering or Fine Tuning: An Empirical Assessment of Large Language Models in Automated Software Engineering Tasks

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Oct 11, 2023

Jun 20, 2024 12:17 PM

DocPrompting: Generating Code by Retrieving the Docs

Large Language Models Are Human-Level Prompt Engineers

https://arxiv.org/abs/2310.10508

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

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Jan 24, 2024

Jun 20, 2024 12:16 PM

Large Language Models Are Human-Level Prompt Engineers

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

https://arxiv.org/abs/2309.17249

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

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Jul 3, 2023

Jun 20, 2024 12:16 PM

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

DocPrompting: Generating Code by Retrieving the Docs

Large Language Models Are Human-Level Prompt Engineers

To be or not to be? an exploration of continuously controllable prompt engineering

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

https://arxiv.org/abs/2306.06211

Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering

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Dec 3, 2023

Jun 20, 2024 12:16 PM

DocPrompting: Generating Code by Retrieving the Docs

Large Language Models Are Human-Level Prompt Engineers

https://arxiv.org/abs/2303.13534

A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models

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Jul 24, 2023

Jun 20, 2024 12:15 PM

DocPrompting: Generating Code by Retrieving the Docs

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

https://arxiv.org/abs/2307.12980

Understanding prompt engineering may not require rethinking generalization

Ready to Publish

Oct 6, 2023

Jun 20, 2024 12:14 PM

ReAct: Synergizing Reasoning and Acting in Language Models

DocPrompting: Generating Code by Retrieving the Docs

https://arxiv.org/abs/2310.03957

To be or not to be? an exploration of continuously controllable prompt engineering

Ready to Publish

Nov 16, 2023

Jun 20, 2024 12:14 PM

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

DocPrompting: Generating Code by Retrieving the Docs

https://arxiv.org/abs/2311.09773

PEACE: Prompt Engineering Automation for CLIPSeg Enhancement in Aerial Robotics

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Dec 8, 2023

Jun 20, 2024 12:14 PM

DocPrompting: Generating Code by Retrieving the Docs

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

https://arxiv.org/abs/2310.000

Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues

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May 17, 2023

Jun 20, 2024 12:13 PM

Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues

DocPrompting: Generating Code by Retrieving the Docs

Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies

SAMAug: Point Prompt Augmentation for Segment Anything Model

SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

https://arxiv.org/abs/2305.16330

Prompt-Engineering and Transformer-based Question Generation and Evaluation

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Oct 29, 2023

Jun 20, 2024 12:12 PM

ReAct: Synergizing Reasoning and Acting in Language Models

DocPrompting: Generating Code by Retrieving the Docs

https://arxiv.org/abs/2310.18867

Prompt Engineering-assisted Malware Dynamic Analysis Using GPT-4

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Dec 13, 2023

Jun 20, 2024 12:12 PM

DocPrompting: Generating Code by Retrieving the Docs

Large Language Models Are Human-Level Prompt Engineers

https://arxiv.org/abs/2312.08317

Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT

Ready to Publish

Jun 19, 2023

Jun 20, 2024 12:11 PM

ReAct: Synergizing Reasoning and Acting in Language Models

DocPrompting: Generating Code by Retrieving the Docs

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

https://arxiv.org/abs/2307.05493

Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies

Ready to Publish

Dec 12, 2023

Jun 20, 2024 12:10 PM

Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

https://arxiv.org/abs/2312.04344

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

Ready to Publish

Nov 9, 2023

Jun 20, 2024 12:10 PM

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

DocPrompting: Generating Code by Retrieving the Docs

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

https://arxiv.org/abs/2312.04344

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

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Aug 14, 2023

Jun 20, 2024 12:09 PM

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation

Chit-Chat or Deep Talk: Prompt Engineering for Process Mining

SAMAug: Point Prompt Augmentation for Segment Anything Model

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models

Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential

SGL-PT: A Strong Graph Learner with Graph Prompt Tuning

State of What Art? A Call for Multi-Prompt LLM Evaluation

https://arxiv.org/abs/2308.07411

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

Ready to Publish

Jun 6, 2024

Jun 20, 2024 12:09 PM

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies

Cases of EFL Secondary Students' Prompt Engineering Pathways to Complete a Writing Task with ChatGPT

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation

Wordflow: Social Prompt Engineering for Large Language Models

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective

A Novel Approach for Rapid Development Based on ChatGPT and Prompt Engineering

Chit-Chat or Deep Talk: Prompt Engineering for Process Mining

SAMAug: Point Prompt Augmentation for Segment Anything Model

SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models

Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness

Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training

Prompt Cache: Modular Attention Reuse for Low-Latency Inference

https://arxiv.org/abs/2405.02664

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

Ready to Publish

Mar 5, 2024

Jun 20, 2024 12:09 PM

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

Exploring Prompt Engineering Practices in the Enterprise

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective

A Novel Approach for Rapid Development Based on ChatGPT and Prompt Engineering

Chit-Chat or Deep Talk: Prompt Engineering for Process Mining

https://arxiv.org/abs/2403.02610

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

Ready to Publish

Mar 23, 2024

Jun 20, 2024 12:08 PM

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

Large Language Models and Prompt Engineering for Biomedical Query Focused Multi-Document Summarisation

Exploring Prompt Engineering Practices in the Enterprise

Wordflow: Social Prompt Engineering for Large Language Models

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective

A Novel Approach for Rapid Development Based on ChatGPT and Prompt Engineering

https://arxiv.org/abs/2403.15875

Exploring Prompt Engineering Practices in the Enterprise

Ready to Publish

Mar 13, 2024

Jun 20, 2024 12:08 PM

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

Exploring Prompt Engineering Practices in the Enterprise

Wordflow: Social Prompt Engineering for Large Language Models

https://arxiv.org/abs/2403.0895

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation

Ready to Publish

Mar 28, 2024

Jun 20, 2024 12:08 PM

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

https://arxiv.org/abs/2403.1910

Wordflow: Social Prompt Engineering for Large Language Models

Ready to Publish

Jan 25, 2024

Jun 20, 2024 12:07 PM

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

Exploring Prompt Engineering Practices in the Enterprise

https://arxiv.org/abs/2401.14447

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Ready to Publish

Feb 5, 2024

Jun 20, 2024 12:07 PM

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

https://arxiv.org/abs/2402.07927

Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective

Ready to Publish

Feb 10, 2024

Jun 20, 2024 12:07 PM

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings

A study on Prompt Design, Advantages and Limitations of ChatGPT for Deep Learning Program Repair

Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT

https://arxiv.org/abs/2306.01798

A Novel Approach for Rapid Development Based on ChatGPT and Prompt Engineering

Ready to Publish

Dec 21, 2023

Jun 20, 2024 12:06 PM

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification

https://arxiv.org/abs/2312.13115

Chit-Chat or Deep Talk: Prompt Engineering for Process Mining

Ready to Publish

Jul 19, 2023

Jun 20, 2024 11:59 AM

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

ChatGPT4PCG 2 Competition: Prompt Engineering for Science Birds Level Generation

How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings

Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness

Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential

A study on Prompt Design, Advantages and Limitations of ChatGPT for Deep Learning Program Repair

Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT

State of What Art? A Call for Multi-Prompt LLM Evaluation

https://arxiv.org/abs/2307.09909

SAMAug: Point Prompt Augmentation for Segment Anything Model

Ready to Publish

Mar 19, 2024

Jun 20, 2024 11:59 AM

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

https://arxiv.org/abs/2307.01187

How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings

Ready to Publish

Nov 27, 2023

Jun 20, 2024 11:50 AM

Chit-Chat or Deep Talk: Prompt Engineering for Process Mining

How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings

Exploring EFL students' prompt engineering in human-AI story writing: an Activity Theory perspective

SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models

Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness

Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential

SGL-PT: A Strong Graph Learner with Graph Prompt Tuning

Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training

Prompt Cache: Modular Attention Reuse for Low-Latency Inference

State of What Art? A Call for Multi-Prompt LLM Evaluation

https://arxiv.org/abs/2305.11853

SAM on Medical Images: A Comprehensive Study on Three Prompt Modes

Ready to Publish

Apr 28, 2023

Jun 20, 2024 11:50 AM

How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings

Prompt Engineering for Transformer-based Chemical Similarity Search Identifies Structurally Distinct Functional Analogues

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

https://arxiv.org/abs/2305.00035

Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models

Ready to Publish

Jun 1, 2023

Featured

Jun 20, 2024 11:49 AM

How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings

Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering

MedPromptExtract (Medical Data Extraction Tool): Anonymization and Hi-fidelity Automated data extraction using NLP and prompt engineering

https://arxiv.org/abs/2305.16223