Stories about Fine-Tuning
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Attention Sensitivity Is Not Enough: Dissociating Attention-Level and Behavioural In-Context Learning under Fine-Tuning
AI InsightThe paper pushes attention sensitivity near its geometric ceiling via regularization, but if behavioral ICL still degrades, the attention proxy cannot replace behavioral evaluation. This suggests that verifying ICL preservation after fine-tuning must return to behavioral accuracy gaps rather than attention shifts alone.Key TakeawayAttention sensitivity is insufficient as a reliable proxy for ICL preservation after fine-tuning; behavioral verification is key.Why It MattersFine-tuning is a common adaptation method but often degrades ICL. If attention-based diagnostics provide false reassurance, developers may underestimate behavioral loss, pushing evaluation standards from proxy metrics to behavioral verification.Who's Affected- AI ResearchersGain a stricter perspective on ICL evaluation, avoiding misleading attention proxy.
- Model DevelopersNeed to monitor behavioral ICL metrics during fine-tuning, not just attention changes.
What's NextWatch for studies directly comparing ICL-GAP before and after ICS optimization; if behavioral gap does not shrink significantly, it would further confirm the insufficiency of attention proxy.Importance 55/100