Verified claim · AI-ML · 100% confidence
ARC-AGI benchmark introduced in: Chollet 2019 — abstraction and reasoning corpus.
Last verified 2026-05-16 · Methodology veritas-v0.1 · cc5df3c14d35fa49
Structured fields
- Subject
- ARC-AGI benchmark
- Predicate
introduced_in- Object
- Chollet 2019 — abstraction and reasoning corpus
- Confidence
- 100%
- Tags
- arc-agi · chollet · benchmark · reasoning · foundational · 2019 · introduced_in
Sources (2)
[1] preprint · arXiv (Chollet / Google) · 2019-11-05
On the Measure of Intelligence“To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems.”
[2] github release · François Chollet · 2019-11-05
ARC-AGI — official François Chollet repository
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// "ARC-AGI benchmark introduced in: Chollet 2019 — abstraction and reasoning corpus."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/cc5df3c14d35fa49.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "ARC-AGI benchmark introduced in: Chollet 2019 — abstraction and reasoning corpus."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_arc_agi_benchmark_fact() -> dict:
"""Fetch the verified SourceScore claim for ARC-AGI benchmark."""
r = httpx.get("https://sourcescore.org/api/v1/claims/cc5df3c14d35fa49.json")
return r.json()