Most benchmark 'model errors' are actually benchmark or grading errors, analysis finds
zainhas · x · 2026-09-16
Commenting on a benchmark error analysis, zainhas notes that the majority of errors across benchmarks are benchmark errors or grading errors, not model errors — "the call is coming from inside the house," highlighting ongoing concerns about LLM eval reliability.
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