arXiv cs.LG
· Papers
Beyond Full-Model Rollback: AuroSFT for Adapter-State Multi-Task Fine-Tuning
arXiv:2608.05250v1 Announce Type: new Abstract: Multi-task supervised fine-tuning (SFT) often casts a heterogeneous data mixture as a single optimization problem, even though different tasks may reach their best generalization at different times. msft exposes this mismatch through task-wise roll-out, exclusion, and rol