88 citations · 119 across the 3 of their papers we have counts for
4 papers
Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting
Marta Skreta, Naruki Yoshikawa, Sebastian Arellano-Rubach +6
Generating low-level robot task plans from high-level natural language instructions remains a challenging problem. Although large language models have shown promising results in ge…
Chemistry Lab Automation via Constrained Task and Motion Planning
Naruki Yoshikawa, Andrew Zou Li, Kourosh Darvish +6
Chemists need to perform many laborious and time-consuming experiments in the lab to discover and understand the properties of new materials. To support and accelerate this process…
Assigning Confidence to Molecular Property Prediction
AkshatKumar Nigam, Robert Pollice, Matthew F. D. Hurley +6
Introduction: Computational modeling has rapidly advanced over the last decades, especially to predict molecular properties for chemistry, material science and drug design. Recentl…
Population-based de novo molecule generation, using grammatical evolution
Naruki Yoshikawa, Kei Terayama, Teruki Honma +2
Automatic design with machine learning and molecular simulations has shown a remarkable ability to generate new and promising drug candidates. Current models, however, still have p…