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arXiv · 2502.15013

Towards Physics-Guided Foundation Models

Majid Farhadloo·Arun Sharma·Mingzhou Yang·Bharat Jayaprakash·William Northrop·Shashi Shekhar
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Abstract

Traditional foundation models are pre-trained on broad datasets to reduce the training resources (e.g., time, energy, labeled samples) needed for fine-tuning a wide range of downstream tasks. However, traditional foundation models struggle with out-of-distribution prediction and can produce outputs that are unrealistic and physically infeasible. We propose the notation of physics-guided foundation models (PGFM), that is, foundation models integrated with broad or general domain (e.g., scientific) physical knowledge applicable to a wide range of downstream tasks.

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Majid Farhadloo, Arun Sharma, Mingzhou Yang, Bharat Jayaprakash, William Northrop, Shashi Shekhar. 2025-04-23. Towards Physics-Guided Foundation Models. https://arxiv.org/abs/2502.15013

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