Rhamba uses region-aware masking strategies and hybrid Attention-Mamba models pretrained on ABIDE fMRI data to achieve top AUROC on schizophrenia and ADHD classification tasks while outperforming prior methods.
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An automated rule-based parser plus LLM pipeline creates a 163k-pair molecular structure-language dataset validated at 98.6% precision on a 2,000-sample subset.
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Rhamba: Region-Aware Hybrid Attention-Mamba Framework for Self-Supervised Learning in Resting-State fMRI
Rhamba uses region-aware masking strategies and hybrid Attention-Mamba models pretrained on ABIDE fMRI data to achieve top AUROC on schizophrenia and ADHD classification tasks while outperforming prior methods.
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A Large-Scale Dataset for Molecular Structure-Language Description via a Rule-Regularized Method
An automated rule-based parser plus LLM pipeline creates a 163k-pair molecular structure-language dataset validated at 98.6% precision on a 2,000-sample subset.