Unverified50% confidenceFactExact time
A study unifies multi-armed bandit regret, sequential testing, best-arm identification, and instance-dependent limits of Markov decision processes (MDPs) into a single chain of proof.
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11/2/2026
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UnverifiedRecommended practices for building a human-annotated set include: sampling by coverage, oversampling failure cases, having two people annotate independently, first measuring human-to-human agreement as an upper bound, adjudicating disagreements into a single gold label, and splitting into a calibration set and a holdout set.65% similarUnverifiedThe study recommends first confirming whether the condition set is robust before debating which similarity metric to use.65% similarVerifiedThe study focuses on examining the impact of three aspects on proof quality: checkpoint selection, verification mechanisms, and iterative refinement of answers.65% similarUnverifiedThe study conducted a formal identifiability analysis, explicitly specifying the conditions under which aggregated observations can identify a constrained instance predictor.65% similarUnverifiedThe study's methodology pre-registered hypotheses, thresholds, and analysis methods, used deterministic regular expressions for scoring rather than a large model as judge, and calculated confidence intervals via bill-level clustered bootstrapping.64% similar
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