Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards. - Katherine Metcalf; Miguel Sarabia; Natalie Mackraz; Barry-John Theobald (CoRL, 2023)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Walter Talbott; Katherine Metcalf; Natalie Mackraz; R. Devon Hjelm; Alexander Toshev (CoRR, 2023)

Large Language Models as Generalizable Policies for Embodied Tasks. - Andrew Szot; Max Schwarzer; Harsh Agrawal; Bogdan Mazoure; Rin Metcalf; Walter Talbott; Natalie Mackraz; R. Devon Hjelm; Alexander T. Toshev (ICLR, 2024)

PREDICT: Preference Reasoning by Evaluating Decomposed preferences Inferred from Candidate Trajectories. - Stephane Aroca-Ouellette; Natalie Mackraz; Barry-John Theobald; Katherine Metcalf (CoRR, 2024)

Evaluating Gender Bias Transfer between Pre-trained and Prompt-Adapted Language Models. - Natalie Mackraz; Nivedha Sivakumar; Samira Khorshidi; Krishna Patel; Barry-John Theobald; Luca Zappella; Nicholas Apostoloff (CoRR, 2024)

Aligning LLMs by Predicting Preferences from User Writing Samples. - Stéphane Aroca-Ouellette; Natalie Mackraz; Barry-John Theobald; Katherine Metcalf (CoRR, 2025)

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs. - Yinong Oliver Wang; Nivedha Sivakumar; Falaah Arif Khan; Rin Metcalf Susa; Adam Golinski; Natalie Mackraz; Barry-John Theobald; Luca Zappella; Nicholas Apostoloff (CoRR, 2025)