Layer-Wise Gate-Controlled Prompt Truncation in a Multimodal Chest X-Ray Classifier
Mixture of Prompt Experts (MoPE) adapts multimodal transformers through input-dependent prompt composition, while retaining a fixed prompt length. We investigate a layer-wise gating extension in a binary chest X-ray classification pilot study. The controller predicts a retention ratio for each sample, averages these ratios within a mini-batch, and uses the resulting integer length to truncate the static and mixed visual prompts. Retained mixed prompts are also scaled by the individual ratios. In one recorded run per configuration, the gated model reached a best validation accuracy of 0.8996, compared with 0.8969 for the fixed-length baseline; the corresponding final values were 0.8963 and...
| Authors | Jingtao Lei, Hongji Li, Dexiang Shu |
|---|---|
| Primary category | cs.LG |
| Published | 6 September 2026 |
| Last updated at source | 6 September 2026 |
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