3 citations · 3 across the 1 of their papers we have counts for
3 papers · 1 filter
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…
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…
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…