LLM benchmarks are largely redundant: fewer tasks suffice for reliable model rankings
kalyan_kpl · x · 2026-11-09
The paper "Are Many Tasks Necessary for General LLM Evaluation?" challenges the practice of averaging scores across many benchmarks. Analyzing 100 LLMs across 13 aggregate tasks and 523 subtasks, the authors find: (1) many benchmarks are highly redundant; (2) rankings show high rank correlation with ALS matrix completion even after masking several task scores; (3) multiple-choice scores can recover rankings on free-form generation tasks; (4) free-form evaluation is not more informative than multiple-choice for general ranking. Conclusion: general-purpose LLM evaluation can be done with far fewer tasks than current practice.
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