4 papers
A Foundation Model for Material Fracture Prediction
Agnese Marcato, Aleksandra Pachalieva, Ryley G. Hill +14
Accurately predicting when and how materials fail is critical to designing safe, reliable structures, mechanical systems, and engineered components that operate under stress. Yet,…
Patchfinder: Leveraging Visual Language Models for Accurate Information Retrieval using Model Uncertainty
Roman Colman, Minh Vu, Manish Bhattarai +4
For decades, corporations and governments have relied on scanned documents to record vast amounts of information. However, extracting this information is a slow and tedious process…
Developing a Foundation Model for Predicting Material Failure
Agnese Marcato, Javier E. Santos, Aleksandra Pachalieva +10
Understanding material failure is critical for designing stronger and lighter structures by identifying weaknesses that could be mitigated. Existing full-physics numerical simulati…
Benchmarking Large Language Models with Integer Sequence Generation Tasks
Daniel O'Malley, Manish Bhattarai, Nishath Rajiv Ranasinghe +2
We present a novel benchmark designed to rigorously evaluate the capabilities of large language models (LLMs) in mathematical reasoning and algorithmic code synthesis tasks. The be…