PRISM: A Geometric Risk Bound for Decomposing Drift into Scale, Shape, and Head

PRISM creates a unified mathematical bound to diagnose how post-training LLM variants drift. It decomposes risk into three measurable axes: scale mismatch, shape mismatch, and head divergence. This allows researchers to pinpoint the exact mechanism causing performance degradation in models like quantized or LoRA-adapted versions.

Open the full episode

More from AI Radio