Adaptive gates in CLIP-style few-shot prompt learning often collapse due to gradient magnitude imbalance and gate degradation, failing to beat fixed prompts.
For each transformer layerd, we maintain textual promptsP (d) t ∈R N×D t and visual promptsP (d) v ∈R N×D v
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When Adaptation Fails: A Gradient-Based Diagnosis of Collapsed Gating in Vision-Language Prompt Learning
Adaptive gates in CLIP-style few-shot prompt learning often collapse due to gradient magnitude imbalance and gate degradation, failing to beat fixed prompts.