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cs.LG2025
Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks
Angelica Chen, Samuel D. Stanton, Frances Ding +6
Although large language models (LLMs) have shown promise in biomolecule optimization problems, they incur heavy computational costs and struggle to satisfy precise constraints. On…
cs.LG2024
Concept Bottleneck Language Models For protein design
Aya Abdelsalam Ismail, Tuomas Oikarinen, Amy Wang +8
We introduce Concept Bottleneck Protein Language Models (CB-pLM), a generative masked language model with a layer where each neuron corresponds to an interpretable concept. Our arc…
cs.LG2024
Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms
Samuel Stanton, Robert Alberstein, Nathan Frey +2
There is a growing body of work seeking to replicate the success of machine learning (ML) on domains like computer vision (CV) and natural language processing (NLP) to applications…