ReLope: From Hidden-State Probing to a Decision Module for Multimodal LLM Routing
Routing balances performance and cost in hybrid systems by escalating selected queries from a lightweight model to a powerful but expensive one. Hidden-state probes provide an effective routing signal by predicting the small model's correctness from hidden states it already computes. Although effective in text-only settings, their behavior on multimodal LLMs (MLLMs) is less understood. We find that correctness is harder to predict from hidden states when questions are paired with images rather than with captions of those images. Two training-free dependence measures, HSIC and label CKA, show the same pattern. We first investigate whether changing hidden states used by the probe improves c...
| Authors | Yaopei Zeng, Congchao Wang, Blake JianHang Chen et al. |
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| Primary category | cs.AI |
| Published | 25 March 2026 |
| Last updated at source | 5 October 2026 |
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