Tag
This paper identifies and formalizes 'inference-time model shift'—a change in conformal score distributions caused by varying inference configurations like quantization and temperature rather than data distribution changes—showing it breaks split-conformal exchangeability and overstates deployment-time coverage across 8 language models and 4 finite-label benchmarks.