1 citations · 1 across the 6 of their papers we have counts for
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SPUS: A Lightweight and Parameter-Efficient Foundation Model for PDEs
Abu Bucker Siddik, Diane Oyen, Alexander Most +2
We introduce Small PDE U-Net Solver (SPUS), a compact and efficient foundation model (FM) designed as a unified neural operator for solving a wide range of partial differential equ…
MORPH: PDE Foundation Models with Arbitrary Data Modality
Mahindra Singh Rautela, Alexander Most, Siddharth Mansingh +6
We introduce MORPH, a modality-agnostic, autoregressive foundation model for partial differential equations (PDEs). MORPH is built on a convolutional vision transformer backbone th…
Lost in OCR Translation? Vision-Based Approaches to Robust Document Retrieval
Alexander Most, Joseph Winjum, Ayan Biswas +4
Retrieval-Augmented Generation (RAG) has become a popular technique for enhancing the reliability and utility of Large Language Models (LLMs) by grounding responses in external doc…
LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study
Nishath Rajiv Ranasinghe, Shawn M. Jones, Michal Kucer +5
Large Language Models (LLMs) are increasingly being leveraged for generating and translating scientific computer codes by both domain-experts and non-domain experts. Fortran has se…