arXiv cs.NE
· Papers
Omega-S: A Functional Resilience Index for LLM Fine-Tuning
arXiv:2608.03887v1 Announce Type: cross Abstract: Fine-tuning a large language model on new data degrades what it previously learned. We present Omega-S, a drop-in penalty computed from the weight matrix alone: it needs no previous-task data, no Fisher matrix and no stored copy of the old weights. It is three lines in