# MindCross: Fast New Subject Adaptation with Limited Data for Cross-subject Video Reconstruction from Brain Signals

arXiv: https://arxiv.org/abs/2511.14196 · HTML: https://mlsanity.com/paper/2511.14196/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Nov 2025.

## Built on by (most cited first, 5 of 5)

- [Let EEG Models Learn EEG](https://mlsanity.com/paper/2605.21280/) (2026)
- [Neural Visual Decoding via Cognitive guided Adaptive Blurring and Information Constrained Alignment](https://mlsanity.com/paper/2605.16418/) (2026)
- [The Visual Target Matters: Learning across the Visual Hierarchy for Brain-to-Image Retrieval](https://mlsanity.com/paper/2609.24136/) (2026)
- [Replaying the Movie in Your Mind Decoding Dynamic Visual Perception and Recall from EEG](https://mlsanity.com/paper/2610.13120/) (2026)
- [Neurons++: A Unified Visual-Stream Framework for Image and Video Reconstruction from fMRI with Neural-to-Visual Interpretability](https://mlsanity.com/paper/2610.13763/) (2026)

## Abstract (arXiv)

Reconstructing video from brain signals is an important brain decoding task. Existing brain decoding frameworks are primarily built on a subject-dependent paradigm, which requires large amounts of brain data for each subject. However, the expensive cost of collecting brain-video data causes severe data scarcity. Although some cross-subject methods being introduced, they often overfocus with subject-invariant information while neglecting subject-specific information, resulting in slow fine-tune-based adaptation strategy. To achieve fast and data-efficient new subject adaptation, we propose MindCross, a novel cross-subject framework. MindCross's N specific encoders and one shared encoder are designed to extract subject-specific and subject-invariant information, respectively. Additionally, a Top-K collaboration module is adopted to enhance new subject decoding with the knowledge learned from previous subjects' encoders. Extensive experiments on fMRI/EEG-to-video benchmarks demonstrate MindCross's efficacy and efficiency of cross-subject decoding and new subject adaptation using only one model.