Sarah M. Burbach

Evaluating Expert Specialization in Mixture-of-Experts Antibody Language Models

This study evaluates MoE architectures for antibody language models, finding token-choice routing improves performance by specializing in CDRH3 residues and enabling efficient pre-training.

A curriculum learning approach to training antibody language models

This paper introduces a curriculum learning approach for training antibody language models, showing that a 650M-parameter model outperforms existing mixed models in downstream tasks.

Data-optimal scaling of paired antibody language models

This study derives a scaling law for antibody language models, showing that performance improvements require both large model size and sufficient data.

Conformational ensemble-based framework enables rapid development of Lassa virus vaccine candidates

This paper uses AI to predict and stabilize the conformational states of Lassa virus GPC, identifying vaccine candidates with improved expression and antigenicity.