From the 1 of 12 linked papers with an AI index.
12 papers
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 paper explores fine‑tuning large language models to predict equilibrium geometries and conformers of small organic and drug‑like molecules, showing that Z‑matrix representation…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +306
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…
Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
Yuanqi Du, Botao Yu, Tianyu Liu +25
There has been unprecedented interest in developing agents that expand the boundary of scientific discovery, primarily by optimizing quantitative objective functions specified by s…
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…
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…