Hi, I have recently been investigating methods used in protein language models and have identified Flow Matching and Mamba as two innovative approaches that could benefit this field. I am interested in understanding whether SimpleFold, described as the first flow-matching-based protein folding model built solely with general-purpose transformer layers, could theoretically adopt Mamba in place of its Transformer backbone to reduce computational complexity and improve efficiency.
This question stems from my exploration of joint protein modeling. I am not requesting an empirical performance comparison between Mamba and Transformers within SimpleFold. Instead, I am seeking a theoretical assessment of feasibility and related insights. My broader research focuses on multimodal large language models for downstream protein tasks, which prompted my interest in SimpleFold’s implementation of Flow Matching.
Hi, I have recently been investigating methods used in protein language models and have identified Flow Matching and Mamba as two innovative approaches that could benefit this field. I am interested in understanding whether SimpleFold, described as the first flow-matching-based protein folding model built solely with general-purpose transformer layers, could theoretically adopt Mamba in place of its Transformer backbone to reduce computational complexity and improve efficiency.
This question stems from my exploration of joint protein modeling. I am not requesting an empirical performance comparison between Mamba and Transformers within SimpleFold. Instead, I am seeking a theoretical assessment of feasibility and related insights. My broader research focuses on multimodal large language models for downstream protein tasks, which prompted my interest in SimpleFold’s implementation of Flow Matching.