Caiqi Zhang

Calibration rankings of LLMs can flip dramatically when accounting for accuracy, challenging long-held beliefs about model performance.

Code generation models can achieve a significant boost in reliability by leveraging a tailored uncertainty estimation framework that outperforms traditional natural language methods.