Capture, Learning, and Synthesis of 3D Speaking Styles. - Daniel Cudeiro; Timo Bolkart; Cassidy Laidlaw; Anurag Ranjan; Michael J. Black (CVPR, 2019)

Functional Adversarial Attacks. - Cassidy Laidlaw; Soheil Feizi (NeurIPS, 2019)

Playing it Safe: Adversarial Robustness with an Abstain Option. - Cassidy Laidlaw; Soheil Feizi (CoRR, 2019)

Perceptual Adversarial Robustness: Defense Against Unseen Threat Models. - Cassidy Laidlaw; Sahil Singla 002; Soheil Feizi (ICLR, 2021)

Uncertain Decisions Facilitate Better Preference Learning. - Cassidy Laidlaw; Stuart Russell 001 (NeurIPS, 2021)

Learning the Preferences of Uncertain Humans with Inverse Decision Theory. - Cassidy Laidlaw; Stuart Russell 001 (CoRR, 2021)

The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models. - Cassidy Laidlaw; Anca D. Dragan (ICLR, 2022)

Bridging RL Theory and Practice with the Effective Horizon. - Cassidy Laidlaw; Stuart J. Russell; Anca D. Dragan (NeurIPS, 2023)

Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. - Lauren H. Cooke; Harvey Klyne; Edwin Zhang; Cassidy Laidlaw; Milind Tambe; Finale Doshi-Velez (Tiny Papers @ ICLR, 2024)

The Effective Horizon Explains Deep RL Performance in Stochastic Environments. - Cassidy Laidlaw; Banghua Zhu; Stuart Russell 001; Anca D. Dragan (ICLR, 2024)

Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. - Anand Siththaranjan; Cassidy Laidlaw; Dylan Hadfield-Menell (ICLR, 2024)

Preventing Reward Hacking with Occupancy Measure Regularization. - Cassidy Laidlaw; Shivam Singhal; Anca D. Dragan (CoRR, 2024)

Correlated Proxies: A New Definition and Improved Mitigation for Reward Hacking. - Cassidy Laidlaw; Shivam Singhal; Anca D. Dragan (ICLR, 2025)

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision. - Yaowen Ye; Cassidy Laidlaw; Jacob Steinhardt (ICLR, 2025)

AssistanceZero: Scalably Solving Assistance Games. - Cassidy Laidlaw; Eli Bronstein; Timothy Guo; Dylan Feng; Lukas Berglund; Justin Svegliato; Stuart Russell 001; Anca D. Dragan (CoRR, 2025)