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arXiv AI By Boheng Liu, Lan Wei, Ziyu Li, Chenghua Duan, Qing Li, Dandan Zhang, Xia Wu

BIDETA: Brain-Inspired Data-Efficient Tactile Adaptation for Unseen Sensors

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BIDETA is a gradient‑free framework that adapts pretrained tactile models to new sensors using only a few labeled target contacts. It preserves pretrained representations while repairing sensor‑dependent feature neighborhoods through rapid support memory, support‑conditioned spectral graphs, and reliability‑gated recurrence. Experiments on multiple datasets show that BIDETA dramatically improves accuracy and speeds up adaptation compared to prior methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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