RPA: Residual Patch-Token Adapter for Image Retrieval from EEG and MEG
Most existing MEG and EEG (M/EEG) visual decoding methods align brain signals with a single global embedding extracted from a pretrained visual encoder, leaving open whether intermediate patch representations, which preserve richer and more granular rich visual information, can improve representation learning. To address this question, we introduce the Residual Patch Adapter (RPA), a lightweight, modular adapter that leverages all patch tokens from an intermediate layer of a ViT visual encoder for alignment. Through extensive ablation analyses, we first show that pooling or masking patch tokens degrades the learned representation, demonstrating that retaining the full set of patch tokens ...
| Authors | Yuhui Jin, Yonghao Song, Bingchuan Liu |
|---|---|
| Primary category | cs.CV |
| Published | 19 September 2026 |
| Last updated at source | 6 October 2026 |
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