4 papers
Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning
Alex Ning, Yen-Ling Kuo, Gabe Gomes
Latent reasoning represents a new development in Transformer language models that has shown potential in compressing reasoning lengths compared to chain-of-thought reasoning. By di…
Pre-trained knowledge elevates large language models beyond traditional chemical reaction optimizers
Robert MacKnight, Jose Emilio Regio, Jeffrey G. Ethier +2
Modern optimization in experimental chemistry employs algorithmic search through black-box parameter spaces. Here we demonstrate that pre-trained knowledge in large language models…
Spectral Manifold Harmonization for Graph Imbalanced Regression
Brenda Nogueira, Gabe Gomes, Meng Jiang +2
Graph-structured data is ubiquitous in scientific domains, where models often face imbalanced learning settings. In imbalanced regression, domain preferences focus on specific targ…
Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs
Daniil A. Boiko, Thiago Reschützegger, Benjamin Sanchez-Lengeling +2
Molecular representation is a critical element in our understanding of the physical world and the foundation for modern molecular machine learning. Previous molecular machine learn…