3 citations · 7 across the 7 of their papers we have counts for
3 papers · 1 filter
Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling
Frank Hu, Shriram Chennakesavalu, Zichen Wang +5
Designing viable drug candidates requires searching a combinatorially large and rugged chemical space for molecules that satisfy multiple, often competing, objectives. Large langua…
Frontier LLMs are effective batch optimizers: Assessing reasoning models in continuous and discrete settings
Frank Hu, Shriram Chennakesavalu, David Graff
Frontier large language models (LLMs) have become attractive priors for optimization due to their large-scale pretraining that enables them to navigate a variety of optimization se…
Aligning Transformers with Continuous Feedback via Energy Rank Alignment
Shriram Chennakesavalu, Frank Hu, Sebastian Ibarraran +1
Searching through chemical space is an exceptionally challenging problem because the number of possible molecules grows combinatorially with the number of atoms. Large, autoregress…