Jiuchong Gao

AuRA achieves superior performance in speech-language tasks by seamlessly integrating audio understanding into LLMs, outperforming traditional methods in both speed and accuracy.

Achieve more human-like and consistent user simulation in Chinese across multiple domains by iteratively refining user profiles with real dialogue data and aligning behavior with a rubric-guided reward model.