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Collections including paper arxiv:2210.03629

DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Paper • 2310.03714 • Published Oct 5, 2023 • 36
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent

Paper • 2312.10003 • Published Dec 15, 2023 • 44
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework

Paper • 2308.08155 • Published Aug 16, 2023 • 9
GAIA: a benchmark for General AI Assistants

Paper • 2311.12983 • Published Nov 21, 2023 • 229

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

Agentic Systems

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27
If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents

Paper • 2401.00812 • Published Jan 1, 2024 • 11
DynaSaur: Large Language Agents Beyond Predefined Actions

Paper • 2411.01747 • Published Nov 4, 2024 • 37
Executable Code Actions Elicit Better LLM Agents

Paper • 2402.01030 • Published Feb 1, 2024 • 168

Agents: An Open-source Framework for Autonomous Language Agents

Paper • 2309.07870 • Published Sep 14, 2023 • 42
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Paper • 2310.18940 • Published Oct 29, 2023
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Paper • 2504.01990 • Published Mar 31 • 302
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 29

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022 • 1
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 21
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021 • 1
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 2

first collection

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

Chain of thought

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

Executable Code Actions Elicit Better LLM Agents

Paper • 2402.01030 • Published Feb 1, 2024 • 168
ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Paper • 2310.03714 • Published Oct 5, 2023 • 36
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent

Paper • 2312.10003 • Published Dec 15, 2023 • 44
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework

Paper • 2308.08155 • Published Aug 16, 2023 • 9
GAIA: a benchmark for General AI Assistants

Paper • 2311.12983 • Published Nov 21, 2023 • 229

A collection of arXiv papers from Chip Huyen's AI Engineering organized by chapter and ordered by when each appears in the book.

Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning

Paper • 2211.04325 • Published Oct 26, 2022 • 1
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 21
On the Opportunities and Risks of Foundation Models

Paper • 2108.07258 • Published Aug 16, 2021 • 1
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Paper • 2204.07705 • Published Apr 16, 2022 • 2

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

first collection

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

Chain of thought

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

Agentic Systems

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27
If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents

Paper • 2401.00812 • Published Jan 1, 2024 • 11
DynaSaur: Large Language Agents Beyond Predefined Actions

Paper • 2411.01747 • Published Nov 4, 2024 • 37
Executable Code Actions Elicit Better LLM Agents

Paper • 2402.01030 • Published Feb 1, 2024 • 168

ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

Agents: An Open-source Framework for Autonomous Language Agents

Paper • 2309.07870 • Published Sep 14, 2023 • 42
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Paper • 2310.18940 • Published Oct 29, 2023
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Paper • 2504.01990 • Published Mar 31 • 302
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent

Paper • 2404.03648 • Published Apr 4, 2024 • 29

Executable Code Actions Elicit Better LLM Agents

Paper • 2402.01030 • Published Feb 1, 2024 • 168
ReAct: Synergizing Reasoning and Acting in Language Models

Paper • 2210.03629 • Published Oct 6, 2022 • 27

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