Yun Yang

SkillSynth's skill graph approach lets you explicitly control the diversity of execution trajectories during terminal task synthesis, leading to more effective agent training.

A single graph foundation model can now achieve state-of-the-art anomaly detection across diverse graph domains, thanks to a new theory of "Anomaly Disassortativity" that tackles domain shift.

Graph-based code representations, largely unexplored in automated patch correctness assessment, crush sequence- and heuristic-based methods, achieving 82.6% accuracy in predicting patch correctness.