Claim · 2024-06-03 · publication · Stated in source · Supported

The paper introduces MMLU-Pro, a dataset that extends the MMLU benchmark with more reasoning-focused questions and expands the answer choices from four to ten.

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What it connects

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark → states its contribution → The paper introduces MMLU-Pro, a dataset that extends the MMLU benchmark with more reasoning-focused questions and expands the answer choices from four to ten.

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Claim and evidence

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmarkstates its contribution ↓The paper introduces MMLU-Pro, a dataset that extends the MMLU benchmark with more reasoning-focused questions and expands the answer choices from four to ten.

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2024-06-03 · publication Records dated 2024 →

Scope and limitsThe paper's own description of its contribution; not an assessment of it.

The evidence 01

primary sourceSupports the claim

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

arXiv · 2024-06-03

Cite the original source

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Source excerpt

“This paper introduces MMLU-Pro, an enhanced dataset designed to extend the mostly knowledge-driven MMLU benchmark by integrating more challenging, reasoning-focused questions and expanding the choice set from four to ten options.”

Location in source arXiv v1, PDF p. 1, abstract

Machine-checked · 2026-10-31

Source details and check notes

Authors: Yubo Wang; Xueguang Ma; Ge Zhang; Yuansheng Ni; Abhranil Chandra; Shiguang Guo; Weiming Ren; Aaran Arulraj; Xuan He; Ziyan Jiang; Tianle Li; Max Ku; Kai Wang; Alex Zhuang; Rongqi Fan; Xiang Yue; Wenhu Chen
Version: arXiv:2406.01574v1, submitted 3 June 2024 (UTC). Retrieved for the candidate pack on 2026-10-28 (SHA-256 9bf7b08bf1c220cb6c1ed0dcafb7d10848a21178137e13dd5e13981d8ecd15e3). The author list is the byline as printed on the first page.
Version date: 2024-06-03
Canonical address: Open the canonical source ↗
Accessed: 2026-10-28
Language: English (en)
Attribution: Yubo Wang and others, “MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark”, 2024-06-03.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, key papers (research/key-papers). The quotation (31 words) matched the text retrieved for the candidate pack on 2026-10-28 (research/key-papers/verification.json). Matching ignored differences of whitespace, case, quotation marks, dashes and line-break hyphens, so the source’s typography can differ. A cross-family machine check (2026-10-30, item B047) found the quotation at its locator. No human editorial review.

Status and meaning

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Relation. A paper or other publication describes its own contribution, quoted from the expression the record names, usually its abstract or introduction. The record is the document’s own description, not an assessment: a claim of priority or novelty it contains is the document’s claim, flagged as such, and says nothing about earlier or later work.

Date. Date of the arXiv version quoted, submitted 3 June 2024 (UTC); later versions may word it differently.

Record ID kp-states-mmlu-pro-more-robust-challenging-2024-1