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Collections including paper arxiv:2404.02575

Collection of resources related to Agents.

Communicative Agents for Software Development

Paper • 2307.07924 • Published Jul 16, 2023 • 2
Self-Refine: Iterative Refinement with Self-Feedback

Paper • 2303.17651 • Published Mar 30, 2023 • 2
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent

Paper • 2312.10003 • Published Dec 15, 2023 • 31
ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 12

Plot2Code: A Comprehensive Benchmark for Evaluating Multi-modal Large Language Models in Code Generation from Scientific Plots

Paper • 2405.07990 • Published 27 days ago • 15
Large Language Models as Planning Domain Generators

Paper • 2405.06650 • Published Apr 2 • 8
AutoCrawler: A Progressive Understanding Web Agent for Web Crawler Generation

Paper • 2404.12753 • Published Apr 19 • 39
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

Paper • 2404.07972 • Published Apr 11 • 41

LM Prompt Engineering

about 13 hours ago

Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models

Paper • 2310.04406 • Published Oct 6, 2023 • 8
Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Paper • 2305.10601 • Published May 17, 2023 • 7
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46
Voyager: An Open-Ended Embodied Agent with Large Language Models

Paper • 2305.16291 • Published May 25, 2023 • 8

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Paper • 2404.12253 • Published Apr 18 • 51
SnapKV: LLM Knows What You are Looking for Before Generation

Paper • 2404.14469 • Published Apr 22 • 23
FlowMind: Automatic Workflow Generation with LLMs

Paper • 2404.13050 • Published Mar 17 • 32

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46

Papers - Yonsei University

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46

Papers - Prompts - Detailed Examples

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46

Papers - Coding - Think and Exectue - 7B vs 13B vs GPT

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46

Papers - Coding - Program of Thoughts (PoT)

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46

Papers - Coding - Think and Execute vs CoT and PoTs

Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models

Paper • 2404.02575 • Published Apr 3 • 46

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