RL: Generic reinforcement learning codebase in TensorFlow. - Bryan M. Li; Alexander I. Cowen-Rivers; Piotr Kozakowski; David Tao; Siddhartha Kamalakara; Nitarshan Rajkumar; Hariharan Sezhiyan; Sicong Huang 001; Aidan N. Gomez (J. Open Source Softw., 2019)

In search of robust measures of generalization. - Gintare Karolina Dziugaite; Alexandre Drouin; Brady Neal; Nitarshan Rajkumar; Ethan Caballero; Linbo Wang 003; Ioannis Mitliagkas; Daniel M. Roy 001 (NeurIPS, 2020)

Pretraining Representations for Data-Efficient Reinforcement Learning. - Max Schwarzer; Nitarshan Rajkumar; Michael Noukhovitch; Ankesh Anand; Laurent Charlin; R. Devon Hjelm; Philip Bachman; Aaron C. Courville (NeurIPS, 2021)

Myriad: a real-world testbed to bridge trajectory optimization and deep learning. - Nikolaus H. R. Howe; Simon Dufort-Labbé; Nitarshan Rajkumar; Pierre-Luc Bacon (NeurIPS, 2022)

Evaluating the Text-to-SQL Capabilities of Large Language Models. - Nitarshan Rajkumar; Raymond Li; Dzmitry Bahdanau (CoRR, 2022)

Reclaiming the Digital Commons: A Public Data Trust for Training Data. - Alan Chan; Herbie Bradley; Nitarshan Rajkumar (AIES, 2023)

Harms from Increasingly Agentic Algorithmic Systems. - Alan Chan; Rebecca Salganik; Alva Markelius; Chris Pang; Nitarshan Rajkumar; Dmitrii Krasheninnikov; Lauro Langosco; Zhonghao He; Yawen Duan; Micah Carroll; Michelle P. Lin; Alex Mayhew; et al. (FAccT, 2023)

Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics. - Shoaib Ahmed Siddiqui; Nitarshan Rajkumar; Tegan Maharaj; David Krueger 001; Sara Hooker (ICLR, 2023)

Visibility into AI Agents. - Alan Chan; Carson Ezell; Max Kaufmann; Kevin Wei; Lewis Hammond; Herbie Bradley; Emma Bluemke; Nitarshan Rajkumar; David Krueger 001; Noam Kolt; Lennart Heim; Markus Anderljung (FAccT, 2024)

IDs for AI Systems. - Alan Chan; Noam Kolt; Peter Wills; Usman Anwar; Christian Schröder de Witt; Nitarshan Rajkumar; Lewis Hammond; David Krueger 001; Lennart Heim; Markus Anderljung (CoRR, 2024)

Open Problems in Technical AI Governance. - Anka Reuel; Ben Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (CoRR, 2024)

Infrastructure for AI Agents. - Alan Chan; Kevin Wei; Sihao Huang; Nitarshan Rajkumar; Elija Perrier; Seth Lazar; Gillian K. Hadfield; Markus Anderljung (Trans. Mach. Learn. Res., 2025)

Open Problems in Technical AI Governance. - Anka Reuel; Benjamin Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (Trans. Mach. Learn. Res., 2025)