Verified claim · AI-ML · 100% confidence
HumanEval benchmark introduced in paper: Evaluating Large Language Models Trained on Code (Chen et al., 2021).
Last verified 2026-05-16 · Methodology veritas-v0.1 · 71ec42731d2c9e0c
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Structured fields
- Subject
- HumanEval benchmark
- Predicate
introduced_in_paper- Object
- Evaluating Large Language Models Trained on Code (Chen et al., 2021)
- Confidence
- 100%
- Tags
- humaneval · benchmark · codex · openai · chen · 2021 · code-generation
Sources (2)
[1] preprint · arXiv (Chen et al., OpenAI) · 2021-07-07
Evaluating Large Language Models Trained on Code“We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities.”
[2] github release · OpenAI · 2021-07-07
openai/human-eval repositoryOpenAI is rated by SourceScore — see its reliability →
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curl https://sourcescore.org/api/v1/claims/71ec42731d2c9e0c.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/71ec42731d2c9e0c.json");
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// "HumanEval benchmark introduced in paper: Evaluating Large Language Models Trained on Code (Chen et al., 2021)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/71ec42731d2c9e0c.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "HumanEval benchmark introduced in paper: Evaluating Large Language Models Trained on Code (Chen et al., 2021)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_humaneval_benchmark_fact() -> dict:
"""Fetch the verified SourceScore claim for HumanEval benchmark."""
r = httpx.get("https://sourcescore.org/api/v1/claims/71ec42731d2c9e0c.json")
return r.json()