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cs.CV2026
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…
cs.CV2025
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…
cs.CV2025
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…