Verified claim · AI-ML · 100% confidence
ReAct (Reasoning + Acting) introduced in paper: ReAct: Synergizing Reasoning and Acting in Language Models (Yao et al., 2022).
Last verified 2026-05-16 · Methodology veritas-v0.1 · fceea64fa7d04d3a
Structured fields
- Subject
- ReAct (Reasoning + Acting)
- Predicate
introduced_in_paper- Object
- ReAct: Synergizing Reasoning and Acting in Language Models (Yao et al., 2022)
- Confidence
- 100%
- Tags
- react · reasoning · agents · tool-use · foundational · 2022 · yao
Sources (2)
[1] preprint · arXiv (Yao, Zhao, Yu, Du, Shafran, Narasimhan, Cao) · 2022-10-06
ReAct: Synergizing Reasoning and Acting in Language Models“We propose ReAct, a general paradigm that combines reasoning and acting with language models for solving diverse language reasoning and decision making tasks.”
[2] official blog · Princeton NLP · 2022-10-06
ReAct project page
Cite this claim
Ready-to-paste citation (Markdown / plain text):
ReAct (Reasoning + Acting) introduced in paper: ReAct: Synergizing Reasoning and Acting in Language Models (Yao et al., 2022). — SourceScore Claim fceea64fa7d04d3a (verified 2026-05-16). https://sourcescore.org/api/v1/claims/fceea64fa7d04d3a.jsonEmbed this claim
Drop this iframe into any blog post, docs page, or knowledge base. The widget renders the signed claim + primary source + click-through to this canonical page. CC-BY 4.0; attribution included.
<iframe src="https://sourcescore.org/embed/claim/fceea64fa7d04d3a/" width="100%" height="360" frameborder="0" loading="lazy" title="ReAct (Reasoning + Acting) introduced in paper: ReAct: Synergizing Reasoning and Acting in Language Models (Yao et al., 2022)."></iframe>Preview: open in new tab
Related claims
Other verified claims sharing tags with this one — useful for LLM retrieval graphs and citation discovery.
Chinchilla scaling laws introduced in paper: Training Compute-Optimal Large Language Models (Hoffmann et al., 2022).
8befcae6bce01a95 · 100% confidence · shares 2 tags (foundational, 2022)
Chain-of-Thought prompting introduced in paper: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (Wei et al., 2022).
3af924da138ff84c · 100% confidence · shares 2 tags (foundational, 2022)
PaLM introduced in paper: PaLM: Scaling Language Modeling with Pathways (Chowdhery et al., 2022).
d58d505fd9d705fe · 100% confidence · shares 2 tags (foundational, 2022)
Imagen introduced in paper: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding (Saharia et al., 2022).
30fdfa95f8684ca5 · 100% confidence · shares 2 tags (foundational, 2022)
Toolformer introduced in: Schick et al. 2023 — self-supervised LLM tool-use.
cd4387e16e2c3e3d · 100% confidence · shares 2 tags (tool-use, agents)
Use this claim in your code
Fetch this signed envelope from your application. The response includes the verbatim excerpt, primary source URLs, and an HMAC-SHA256 signature you can verify locally for audit trails.
cURL
curl https://sourcescore.org/api/v1/claims/fceea64fa7d04d3a.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/fceea64fa7d04d3a.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "ReAct (Reasoning + Acting) introduced in paper: ReAct: Synergizing Reasoning and Acting in Language Models (Yao et al., 2022)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/fceea64fa7d04d3a.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "ReAct (Reasoning + Acting) introduced in paper: ReAct: Synergizing Reasoning and Acting in Language Models (Yao et al., 2022)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_react_reasoning_acting_fact() -> dict:
"""Fetch the verified SourceScore claim for ReAct (Reasoning + Acting)."""
r = httpx.get("https://sourcescore.org/api/v1/claims/fceea64fa7d04d3a.json")
return r.json()