Decoding Partial Differential Equations: Cross-Modal Adaptation of Decoder-only Models to PDEs

ArXi:2510.05278v2 Announce Type: replace While large language models are primarily used on natural language tasks, they have also shown great promise when adapted to new modalities, e.g., for scientific machine learning tasks. Most proposed approaches for such cross-modal adaptation of language models focus on encoder-only transformer model architectures, despite decoder-only architectures being far popular for language tasks in recent years, and being trained at much larger scales.