5 papers
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…
ARCS: Agentic Retrieval-Augmented Code Synthesis with Iterative Refinement
Manish Bhattarai, Miguel Cordova, Minh Vu +3
We present Agentic Retrieval-Augmented Code Synthesis (ARCS), a system that improves LLM-based code generation without fine-tuning. ARCS operates through a budgeted synthesize-exec…
The Transparent Earth: A Multimodal Foundation Model for the Earth's Subsurface
Arnab Mazumder, Javier E. Santos, Noah Hobbs +2
We present the Transparent Earth, a transformer-based architecture for reconstructing subsurface properties from heterogeneous datasets that vary in sparsity, resolution, and modal…
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…
Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation
Manish Bhattarai, Minh Vu, Javier E. Santos +2
We introduce a novel method to enhance cross-language code translation from Fortran to C++ by integrating task-specific embedding alignment into a Retrieval-Augmented Generation (R…