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

ArXi:2505.11758v2 Announce Type: replace-cross 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 -set geometry. We