Adaptive gates in CLIP-style few-shot prompt learning often collapse due to gradient magnitude imbalance and gate degradation, failing to beat fixed prompts.
In MoE architectures, gating routes among high-capacity expert networks whose parameters are fully trainable and receive strong gradient signals through deep activation paths
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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.