3 papers
cs.LG2025
A study of EHVI vs fixed scalarization for molecule design
Anabel Yong, Austin Tripp, Layla Hosseini-Gerami +1
Multi-objective Bayesian optimization (MOBO) provides a principled framework for navigating trade-offs in molecular design. However, its empirical advantages over scalarized altern…
cs.CL2025
Enhancing Instruction-Following Capabilities in Seq2Seq Models: DoLA Adaptations for T5
Huey Sun, Anabel Yong, Lorenzo Gilly +1
Encoder-decoder models such as FLAN-T5 are finetuned to follow instructions, but often fail when the instructions conflict with memorized continuations ingrained during training. T…
cs.LG2025
Multi-Objective Bayesian Optimization with Independent Tanimoto Kernel Gaussian Processes for Diverse Pareto Front Exploration
Anabel Yong
We present GP-MOBO, a novel multi-objective Bayesian Optimization algorithm that advances the state-of-the-art in molecular optimization. Our approach integrates a fast minimal pac…