Establish tightness theory for more general loss functions
Establish the tightness theory of Occupancy-based Quantile Risk Control for more general loss functions that do not necessarily satisfy the ideal continuity and density conditions required by the current convergence analysis.
References
We leave the establishment of the OQRC tightness theory for more general loss functions to future work.
Adaptive conformal inference gives long-run coverage for a future calibration score $s_{t}$. It does not, without further argument, yield a bound on the distance between two population functionals, $|CVaR{p_\theta}\alpha-CVaR{P}\alpha|\le q_t(\delta')$. Closing that gap requires (i) a precise statement of how the score of Definition~\ref{def:score} identifies the population CVaR difference, in particular a monotone link between score quantiles and that difference, and (ii) an argument that each adaptively proposed refinement attempt is individually valid at level $\delta/B$ before the union bound is applied over attempts. We have neither, and statement~\ref{thm:certified} should be read as conditional on that link, which is why it is not labelled a theorem.