Taha Entesari

Beyond Average Safety: Chance-Constrained LLM Fine-tuning

This work proposes a chance-constrained formulation for safety-preserving fine-tuning that limits the fraction of safety examples whose degradation relative to a reference model exceeds a prescribed threshold and develops a constraint-aware gradient descent method that treats the majorized constraint as a safe set in p...