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Evidence record 13735 · automatically gathered

Evolution-Aware MSA Reasoning for Subsampling via Factor Graphs

Multiple Sequence Alignments (MSAs) provide protein language models with explicit evolutionary context, but their large depth makes subsampling unavoidable under limited token budgets. Existing strategies, including random selection, identity-based filtering, and diversity-driven sampling, are effective heuristics, yet provide limited control over the evolutionary signals retained in the subset. In this work, we recast MSA subsampling as an explicit optimization problem, where key evolutionary m

Record details

Published: 24 July 2026
Source: arXiv cs.LG
Category: Research
Topics: Biotech
Retrieved: 27 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (24 July 2026), “Evolution-Aware MSA Reasoning for Subsampling via Factor Graphs,” evidence record 13735, https://ethics.ai/record/13735 (originally published by arXiv cs.LG).

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