Linchao Zhu

This work introduces a novel framework that learns physical sample residuals instead of direct mappings for PDE solving, significantly improving neural operator generalization in data-limited scenarios.

Code Graph Models (CGMs) innovatively integrate both semantic and structural information from code repositories into LLMs, enabling effective repository-level coding tasks without relying on agents or closed-source models.