Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense. - Jingyuan Wang 001; Yufan Wu; Mingxuan Li 001; Xin Lin; Junjie Wu 001; Chao Li 001 (KDD, 2020)

Detecting and Recovering Adversarial Examples: An Input Sensitivity Guided Method. - Mingxuan Li 001; Jingyuan Wang 001; Yufan Wu (CoRR, 2020)

Towards Sample Efficient Agents through Algorithmic Alignment. - Mingxuan Li 001; Michael L. Littman (CoRR, 2020)

Towards Sample Efficient Agents through Algorithmic Alignment (Student Abstract). - Mingxuan Li 001; Michael L. Littman (AAAI, 2021)

Learning Generalizable Behavior via Visual Rewrite Rules. - Yiheng Xie; Mingxuan Li 001; Shangqun Yu; Michael L. Littman (CoRR, 2021)

Causally Aligned Curriculum Learning. - Mingxuan Li 001; Junzhe Zhang 001; Elias Bareinboim (ICLR, 2024)