SourceScore

Verified claim · AI-ML · 100% confidence

ReAct prompting pattern introduced in: Yao et al. 2022 — synergizing reasoning and acting in language models.

Last verified 2026-05-16 · Methodology veritas-v0.1 · 95193a0b79c777e8

Structured fields

Subject
ReAct prompting pattern
Predicate
introduced_in
Object
Yao et al. 2022 — synergizing reasoning and acting in language models
Confidence
100%
Tags
react · yao · princeton · prompting · agent · foundational · iclr · 2022 · introduced_in

Sources (2)

  1. [1] preprint · arXiv / ICLR 2023 (Yao, Zhao, Yu, Du, Shafran, Narasimhan, Cao / Princeton + Google Brain) · 2022-10-06

    ReAct: Synergizing Reasoning and Acting in Language Models
    We present an approach that uses 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.
  2. [2] peer reviewed · ICLR 2023 · 2023-05-01

    ReAct — ICLR 2023 OpenReview

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ReAct prompting pattern introduced in: Yao et al. 2022 — synergizing reasoning and acting in language models. — SourceScore Claim 95193a0b79c777e8 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/95193a0b79c777e8.json

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LangChain (retrieve-then-cite)

from langchain_core.tools import tool import httpx @tool def get_react_prompting_pattern_fact() -> dict: """Fetch the verified SourceScore claim for ReAct prompting pattern.""" r = httpx.get("https://sourcescore.org/api/v1/claims/95193a0b79c777e8.json") return r.json()