Lu Niu

Noise-Aware Few-Shot Learning through Bi-directional Multi-View Prompt Alignment

Vision-language models offer strong few-shot capability through prompt tuning but remain vulnerable to noisy labels, which can corrupt prompts and degrade cross-modal alignment. Existing approaches struggle because they often lack the ability to model fine-grained semantic cues and to adaptively sep