Skip to content
English

Switch theme

arXiv 2610.26802 · cs.LG · 2026-10-19

Scaling Parameter-Efficient Fine-Tuning for Brain Encoding

Zhuofan Josh Ying, Guanglong Sun, Nolan Ho, Kieran Liu, Rui Yang, Andrew Chen, Nikolaus Kriegeskorte, Pony Ma and 1 more

Mind Lab

In latest · #129 2026-W43 #7 (in progress) Added on 2026-10-21

One-line takeaway

Uses parameter-efficient fine-tuning to adapt multimodal backbones of up to 104B for brain encoding, better predicting neural responses.

用参数高效微调把最大 104B 的多模态模型适配到脑编码任务,更准确地预测大脑对刺激的反应。

237HF upvotes
–GitHub stars
0Citations (Semantic Scholar)
56.8Buzz score

Read on arXiv PDF Hugging Face discussion

About this data

Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.

The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.

Data updated: Latest AI papers(UTC+8)