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Scaling Parameter-Efficient Fine-Tuning for Brain Encoding

230 upvotes · 19 OCT 2026 · Zhuofan Josh Ying, Guanglong Sun, Nolan Ho et al.

This paper develops a method to efficiently fine-tune large pretrained models for brain encoding, allowing for the adaptation of models with up to 104B parameters. Practitioners might care because this approach enables better performance and interpretability for brain encoding tasks.

brain encodingcontinual learningneural dataparameter-efficient fine-tuningmultimodal models