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arXiv Machine Learning By Maryam Rahimimovassagh, Ivan Garibay, Niloofar Yousefi

Beyond Tokens: Probing Higher-Order Epistasis in Learned Protein Representations

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The paper introduces ORBIT, a framework for probing higher‑order epistasis in protein representations. ORBIT validates Walsh‑based diagnostics on synthetic landscapes, then applies them to the GB1 fitness landscape, comparing several models including ridge regression, MLPs, and Residual Interaction Tokenization (RIT). While no architecture differences were found in overall prediction performance, RIT notably increased pairwise token‑level accessibility, and deeper MLPs improved higher‑order functional recovery, revealing representation‑level changes hidden by conventional metrics.

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