3 citations · 7 across the 14 of their papers we have counts for
5 papers · 1 filter
How Well Can Frontier Large Language Models Generate Structures? High Quality Prediction of Molecular Geometries with Help from Fine-Tuning
Joseph M. Cavanagh, Jonathan B. Arnold, Giovanni Battista Alteri +2
The power of Large Language Models (LLMs) has led us to investigate how they might be fine-tuned for learning the "language of molecular geometry". The fine-tuning of the LLMs usin…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +355
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
Towards Diverse Scientific Hypothesis Search with Large Language Models
Haorui Wang, Parshin Shojaee, Kazem Meidani +7
Large language models (LLMs) are on the rise for accelerating scientific discovery, most recently in advanced tasks such as generating valid scientific hypotheses. Yet in many disc…
DrugPlayGround: Benchmarking Large Language Models and Embeddings for Drug Discovery
Tianyu Liu, Sihan Jiang, Fan Zhang +3
Large language models (LLMs) are in the ascendancy for research in drug discovery, offering unprecedented opportunities to reshape drug research by accelerating hypothesis generati…
Machine-Learned Leftmost Hessian Eigenvectors for Robust Transition State Finding
Guanchen Wu, Chung-Yueh Yuan, Kareem Hegazy +2
The reliable determination of transition states (TSs) benefits from second-order information for robust convergence and validation, but the computational expense of Hessians prohib…