mlsanityData to 7 Oct 2026

ReAct: Synergizing Reasoning and Acting in Language Models

arXiv 2210.03629 ↗First posted 6 Oct 2022cs.CL cs.AI cs.LGcited by 8,355

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

While large language models (LLMs) have demonstrated impressive capabilities across tasks in language understanding and interactive decision making, their abilities for reasoning (e.g. chain-of-thought prompting) and acting (e.g. action plan generation) have primarily been studied as separate topics. In this paper, we explore the use of LLMs to generate both reasoning traces and task-specific actions in an interleaved manner, allowing for greater synergy between the two: reasoning traces help the model induce, track, and update action plans as well as handle exceptions, while actions allow it to interface with external sources, such as knowledge bases or environments, to gather additional information. We apply our approach, named ReAct, to a diverse set of language and decision making tasks and demonstrate its effectiveness over state-of-the-art baselines, as well as improved human interpretability and trustworthiness over methods without reasoning or acting components. Concretely, on question answering (HotpotQA) and fact verification (Fever), ReAct overcomes issues of hallucination and error propagation prevalent in chain-of-thought reasoning by interacting with a simple Wikipedia API, and generates human-like task-solving trajectories that are more interpretable than baselines without reasoning traces. On two interactive decision making benchmarks (ALFWorld and WebShop), ReAct outperforms imitation and reinforcement learning methods by an absolute success rate of 34% and 10% respectively, while being prompted with only one or two in-context examples. Project site with code: https://react-lm.github.io

Key facts. Cited by 8,355 papers in the map (data through 7 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 33 of its 65 references that are in the map. First posted on arXiv 6 Oct 2022.

Builds on

33 of 65 references.

Closest ancestors · 3

Same direction, newest first

  1. 2022Faithful Reasoning Using Large Language Models30 Aug
  2. 2022Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning19 May
  3. 2021Show Your Work: Scratchpads for Intermediate Computation with Language Models30 Nov

Other references · 30

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  5. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  6. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  7. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
  8. 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,302
  9. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
  10. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Modelscited by 1,397
  11. 2018FEVER: a large-scale dataset for Fact Extraction and VERificationcited by 1,362
  12. 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,197
18 more
  1. 2020ALFWorld: Aligning Text and Embodied Environments for Interactive Learningcited by 1,143
  2. 2022Inner Monologue: Embodied Reasoning through Planning with Language Modelscited by 1,057
  3. 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,029
  4. 2019ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Taskscited by 773
  5. 2019ELI5: Long Form Question Answeringcited by 567
  6. 2022Improving alignment of dialogue agents via targeted human judgementscited by 527
  7. 2020A Simple Language Model for Task-Oriented Dialoguecited by 331
  8. 2022Pre-Trained Language Models for Interactive Decision-Makingcited by 220
  9. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 197
  10. 2022Internet-augmented language models through few-shot prompting for open-domain question answeringcited by 131
  11. 2022Text and Patterns: For Effective Chain of Thought, It Takes Two to Tangocited by 128
  12. 2022Rationale-Augmented Ensembles in Language Modelscited by 111
  13. 2020Keep CALM and Explore: Language Models for Action Generation in Text-based Gamescited by 108
  14. 2022Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completioncited by 102
  15. 2020Imitating Interactive Intelligencecited by 55
  16. 2021Adaptive Information Seeking for Open-Domain Question Answeringcited by 29
  17. 2021Language Models are Few-Shot Butlerscited by 27
  18. 2021LILA: Language-Informed Latent Actionscited by 27

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 12; 2023: 456; 2024: 1112; 2025: 2083; 2026: 4692.

8,355 papers.

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  5. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  6. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  7. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
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  9. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
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  6. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,295
  7. 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,280
  8. 2023AgentBench: Evaluating LLMs as Agentscited by 1,211
  9. 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,210
  10. 2023SGLang: Efficient Execution of Structured Language Model Programscited by 1,107
  11. 2024ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Toolscited by 1,096
  12. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,057
  13. 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,054
  14. 2024OpenHands: An Open Platform for AI Software Developers as Generalist Agentscited by 956
  15. 2024Large Language Monkeys: Scaling Inference Compute with Repeated Samplingcited by 946
  16. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 911
  17. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
  18. 2023ExpeL: LLM Agents Are Experiential Learnerscited by 814
  19. 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 803
  20. 2025AlphaEvolve: A coding agent for scientific and algorithmic discoverycited by 763
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  22. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
  23. 2023Measuring Faithfulness in Chain-of-Thought Reasoningcited by 668
  24. 2024A Survey on Large Language Models for Code Generationcited by 646
  25. 2022PAL: Program-aided Language Modelscited by 635
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  30. 2023AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviorscited by 580
  31. 2023API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMscited by 574
  32. 2023Prompt Injection attack against LLM-integrated Applicationscited by 568
  33. 2023Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Modelscited by 551
  34. 2023Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Modelscited by 550
  35. 2024Executable Code Actions Elicit Better LLM Agentscited by 537
  36. 2024Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inferencecited by 527
  37. 2023Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolutioncited by 521
  38. 2023Identifying the Risks of LM Agents with an LM-Emulated Sandboxcited by 514

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  4. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debate
  5. 2025On the Same Wavelength? Evaluating Pragmatic Reasoning in Language Models across Broad Concepts
  6. 2025Theorem-of-Thought: A Multi-Agent Framework for Abductive, Deductive, and Inductive Reasoning in Language Models
  7. 2024Synergy-of-Thoughts: Eliciting Efficient Reasoning in Hybrid Language Models
  8. 2025Reasoning Strategies in Large Language Models: Can They Follow, Prefer, and Optimize?