Rujie Yin

ST-PARM improves multi-objective protein design by aligning a frozen language model with user-specified trade-offs using a reward model that handles uncertainty and achieves broader Pareto coverage.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

The paper investigates whether multi-modal data and auxiliary tasks improve inter-protein contact prediction, finding that multi-modal inputs enhance precision but auxiliary tasks have limited benefits.