Nitarshan Rajkumar

21 papers A* 4C 1Journal 14Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Infrastructure for AI Agents.
CoRR
Alan Chan, Kevin Wei, Sihao Huang, Nitarshan Rajkumar, Elija Perrier, Seth Lazar, Gillian K. Hadfield, Markus Anderljung
2025 J jnl
Infrastructure for AI Agents.
Trans. Mach. Learn. Res.
Alan Chan, Kevin Wei, Sihao Huang, Nitarshan Rajkumar, Elija Perrier, Seth Lazar, Gillian K. Hadfield, Markus Anderljung
2025 J jnl
Open Problems in Technical AI Governance.
Trans. Mach. Learn. Res.
Anka Reuel, Benjamin Bucknall, Stephen Casper, Timothy Fist, Lisa Soder, Onni Aarne, Lewis Hammond, Lujain Ibrahim, Alan Chan, Peter Wills, Markus Anderljung, Ben Garfinkel, Lennart Heim, Andrew Trask, Gabriel Mukobi, Rylan Schaeffer, Mauricio Baker, Sara Hooker, Irene Solaiman, Sasha Luccioni, Nitarshan Rajkumar, Nicolas Moës, Jeffrey Ladish, David Bau, Paul Bricman, Neel Guha, Jessica Newman, Yoshua Bengio, Tobin South, Alex Pentland, Sanmi Koyejo, Mykel J. Kochenderfer, Robert Trager
2024 J jnl
IDs for AI Systems.
CoRR
Alan Chan, Noam Kolt, Peter Wills, Usman Anwar, Christian Schröder de Witt, Nitarshan Rajkumar, Lewis Hammond, David Krueger, Lennart Heim, Markus Anderljung
2024 J jnl
Open Problems in Technical AI Governance.
CoRR
Anka Reuel, Ben Bucknall, Stephen Casper, Timothy Fist, Lisa Soder, Onni Aarne, Lewis Hammond, Lujain Ibrahim, Alan Chan, Peter Wills, Markus Anderljung, Ben Garfinkel, Lennart Heim, Andrew Trask, Gabriel Mukobi, Rylan Schaeffer, Mauricio Baker, Sara Hooker, Irene Solaiman, Alexandra Sasha Luccioni, Nitarshan Rajkumar, Nicolas Moës, Jeffrey Ladish, Neel Guha, Jessica Newman, Yoshua Bengio, Tobin South, Alex Pentland, Sanmi Koyejo, Mykel J. Kochenderfer, Robert Trager
2024 — conf
Visibility into AI Agents.
FAccT
Alan Chan, Carson Ezell, Max Kaufmann, Kevin Wei, Lewis Hammond, Herbie Bradley, Emma Bluemke, Nitarshan Rajkumar, David Krueger, Noam Kolt, Lennart Heim, Markus Anderljung
2024 J jnl
Visibility into AI Agents.
CoRR
Alan Chan, Carson Ezell, Max Kaufmann, Kevin Wei, Lewis Hammond, Herbie Bradley, Emma Bluemke, Nitarshan Rajkumar, David Krueger, Noam Kolt, Lennart Heim, Markus Anderljung
2023 — conf
Harms from Increasingly Agentic Algorithmic Systems.
FAccT
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, Katherine M. Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj
2023 J jnl
Harms from Increasingly Agentic Algorithmic Systems.
CoRR
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, Katherine M. Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj
2023 A* conf
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics.
ICLR
Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, Sara Hooker
2023 C conf
Reclaiming the Digital Commons: A Public Data Trust for Training Data.
AIES
Alan Chan, Herbie Bradley, Nitarshan Rajkumar
2023 J jnl
Reclaiming the Digital Commons: A Public Data Trust for Training Data.
CoRR
Alan Chan, Herbie Bradley, Nitarshan Rajkumar
2022 J jnl
Evaluating the Text-to-SQL Capabilities of Large Language Models.
CoRR
Nitarshan Rajkumar, Raymond Li, Dzmitry Bahdanau
2022 J jnl
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics.
CoRR
Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, Sara Hooker
2022 A* conf
Myriad: a real-world testbed to bridge trajectory optimization and deep learning.
NeurIPS
Nikolaus H. R. Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon
2022 J jnl
Myriad: a real-world testbed to bridge trajectory optimization and deep learning.
CoRR
Nikolaus H. R. Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon
2021 A* conf
Pretraining Representations for Data-Efficient Reinforcement Learning.
NeurIPS
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
2021 J jnl
Pretraining Representations for Data-Efficient Reinforcement Learning.
CoRR
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
2020 J jnl
In Search of Robust Measures of Generalization.
CoRR
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy
2020 A* conf
In search of robust measures of generalization.
NeurIPS
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy
2019 J jnl
RL: Generic reinforcement learning codebase in TensorFlow.
J. Open Source Softw.
Bryan M. Li, Alexander I. Cowen-Rivers, Piotr Kozakowski, David Tao, Siddhartha Kamalakara, Nitarshan Rajkumar, Hariharan Sezhiyan, Sicong Huang, Aidan N. Gomez