AINeutralarXiv – CS AI · 4h ago6/10
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What Do Language Priors Contribute to Darcy-Flow Inversion? A Mechanistic Audit
Researchers demonstrate that natural language descriptions can significantly improve machine learning models solving inverse problems in hydrogeology, reducing reconstruction error by 81% compared to models without text conditioning. The study reveals that categorical geological classifications carry the most value, while detailed geometric descriptions provide secondary benefits, establishing language as a practical interface for encoding domain expertise into learned solvers.