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Jong-Hwan Lee

2 accepted papers

2026

BIT-LLM: Brain Instruction Tuned LLM with persistent Cross-Attention for fMRI-to-Text Decoding

ICML 2026poster

Decoding fMRI into natural language is challenging because strong, pre-trained language priors can dominate autoregressive generation, obscuring whether a model truly utilizes neural evidence. We introduce BIT-LLM, which exposes fMRI-derived tokens as a persistent key–value memory through interleave…

Cited by 0SourceScholar
2017

Evaluation of weight sparsity regularizion schemes of deep neural networks applied to functional neuroimaging data

ICASSP 2017accepted

The paper presented a systematic evaluation of the weight sparsity regularization schemes for the deep neural networks applied to the whole brain resting-state functional magnetic resonance imaging data. The weight sparsity regularization was deployed between the visible and hidden layers of the Gau…

Cited by 0SourceScholar