AI RESEARCH

Non-monotonicity in Conformal Risk Control

arXiv CS.LG

ArXi:2604.01502v1 Announce Type: cross Conformal risk control (CRC) provides distribution-free guarantees for controlling the expected loss at a user-specified level. Existing theory typically assumes that the loss decreases monotonically with a tuning parameter that governs the size of the prediction set. This assumption is often violated in practice, where losses may behave non-monotonically due to competing objectives such as coverage and efficiency.