The age of secrecy and unfairness in recidivism prediction. - Cynthia Rudin; Caroline Wang; Beau Coker (CoRR, 2018)

In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction. - Caroline Wang; Bin Han; Bhrij Patel; Feroze Mohideen; Cynthia Rudin (CoRR, 2020)

UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions. - Patrick MacAlpine; Bo Liu 042; William Macke; Caroline Wang; Peter Stone 001 (RoboCup, 2021)

DM2: Distributed Multi-Agent Reinforcement Learning for Distribution Matching. - Caroline Wang; Ishan Durugkar; Elad Liebman; Peter Stone 001 (CoRR, 2022)

DM²: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching. - Caroline Wang; Ishan Durugkar; Elad Liebman; Peter Stone 001 (AAAI, 2023)

D-Shape: Demonstration-Shaped Reinforcement Learning via Goal-Conditioning. - Caroline Wang; Garrett Warnell; Peter Stone 001 (AAMAS, 2023)

Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning. - Zizhao Wang; Caroline Wang; Xuesu Xiao; Yuke Zhu; Peter Stone 001 (AAAI, 2024)

N-Agent Ad Hoc Teamwork. - Caroline Wang (IJCAI, 2024)

N-agent Ad Hoc Teamwork. - Caroline Wang; Arrasy Rahman; Ishan Durugkar; Elad Liebman; Peter Stone 001 (NeurIPS, 2024)

ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork. - Caroline Wang; Arrasy Rahman; Jiaxun Cui; Yoonchang Sung; Peter Stone 001 (CoRR, 2025)

Sequence Modeling for N-Agent Ad Hoc Teamwork. - Caroline Wang; Di Yang Shi; Elad Liebman; Ishan Durugkar; Arrasy Rahman; Peter Stone 001 (CoRR, 2025)