Koushik Howlader

bioMoR: Biology-Guided Mixture-of-Recursions for Effective Genomic Learning

This work proposes bioMoR, which is the first framework to apply MoR to gene-level and pathway-level learning, and identifies three locations for integrating structured biological knowledge within an MoR backbone: graph-based information sharing refines token embeddings, a structural bias guides self-attention toward biologically related tokens, and a graph-aware router uses neighborhood information to determine each token's recursion depth.