3 papers
cs.AI2026
A foundation model of numerical intelligence with cross-disciplinary generalization
Chenghan Wu, Zongmin Yu, Liu Yang
Intelligence is commonly understood as the ability to acquire and apply knowledge, adapt to unfamiliar situations and solve new problems. Large language models exhibit this capacit…
cs.LG2026
Chain of Operators: An Inference-Time Harness for In-Context Operator Learning
Minghui Yang, Chenghan Wu, Ling Guo +1
While scientific foundation models show immense promise in accelerating physical simulations and numerical forecasting, they remain notoriously brittle when encountering out-of-dis…
cs.LG2026
Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction
Chenghan Wu, Zongmin Yu, Boai Sun +1
In-context operator learning enables neural networks to infer solution operators from contextual examples without weight updates. While prior work has demonstrated the effectivenes…