Beyond saturated benchmarks: a researcher's case for continuously evolving, transfer-measuring evals
novasarc01 · x · 2026-11-12
novasarc01 argues most saturated benchmarks suffer distribution-level overfitting beyond contamination. He proposes continuously evolving benchmarks with unseen task families and open-ended environments that measure learning efficiency and transfer — how well benchmark-targeted training generalizes to independently authored tasks. Drawing on experience generating synthetic tasks, he notes creating problems requiring different reasoning is far harder than generating more problems, and suggests a control group to separate benchmark-specific training from real capability gains, plus measuring OOD skill acquisition via dynamic benchmarks.
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