Remark. Task-level success and coverage [ftip-005W]
Remark. Task-level success and coverage [ftip-005W]
Increasing probability mass on known solutions need not increase coverage of the task family. Pass-at-\(k\) and related support-sensitive measurements motivate this distinction. Sections 3--5 of Does reinforcement learning really incentivize reasoning capacity in LLMs beyond the base model?[yue2025does] and Sections 2--3 of Understanding r1-zero-like training: A critical perspective[liu2025understanding] compare post-training behavior with base-model support and discuss why response accuracy alone may overstate what RL creates beyond a base model.
The threshold \(\alpha \), inference budget, task law, and success predicate must all be reported. Finite samples estimate this quantity; they do not reveal the unobserved tail without assumptions.