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arXiv Open Access 2025

Towards Physics-Guided Foundation Models

Majid Farhadloo Arun Sharma Mingzhou Yang Bharat Jayaprakash William Northrop +1 lainnya
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Abstrak

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.

Topik & Kata Kunci

cs.LG cs.AI

Penulis (6)

M

Majid Farhadloo

A

Arun Sharma

M

Mingzhou Yang

B

Bharat Jayaprakash

W

William Northrop

S

Shashi Shekhar

Format Sitasi

APA MLA BibTeX
Farhadloo, M., Sharma, A., Yang, M., Jayaprakash, B., Northrop, W., Shekhar, S. (2025). Towards Physics-Guided Foundation Models. https://arxiv.org/abs/2502.15013

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Tahun Terbit
2025
Bahasa
en
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arXiv
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Open Access ✓