3 papers
cs.LG2026
Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design
Shriram Chennakesavalu, Kirill Shmilovich, Hayley Weir +5
Large Language Models (LLMs) have the potential to accelerate small molecule drug design due to their ability to reason about information from diverse sources and formats. However,…
physics.chem-ph2026
Scaling Transferable Coarse-graining with Mean Force Matching
Abigail Park, Shriram Chennakesavalu, Grant M. Rotskoff
Coarse-grained molecular dynamics often sacrifices accuracy and transferability for computational efficiency, but the use of machine learned potentials is helping coarse-grained mo…
cs.LG2025
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…