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What’s in Pass@K?
Published:
Pass@k is ubiquitous in evaluating reasoning models, but the metric is more subtle than it appears. Computing it correctly requires the unbiased estimator, and the nonlinearity of pass@k means it effectively upweights hard problems compared to pass@1.
Implementing Process Rewards in VeRL
Published:
Using process rewards in VeRL requires advantage estimators that preserve token-level structure. Most standard algorithms collapse rewards to scalars, defeating the purpose of fine-grained credit assignment.
Understanding Length Dynamics in RL Training
Published:
An empirical investigation into what drives output length growth during RL training, revealing that dataset difficulty composition is the primary driver behind the ‘overthinking’ phenomenon.
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