Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning 事件

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning arXiv:2505.11758v2 Announce Type: replace Abstract: Few-shot adaptation of vision-language models remains fundamentally limited by how negative class signals are handled at inference. Existing methods apply uniform negative suppression across all queries, ignoring that the most damaging confusions are query-specific and shift with support-set geometry. We introduce SCAN (Selective Confusion-Aware Neg