Nitarshan Rajkumar

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 18

Top Topics

Top Venues

Publications

Alan Chan, Carson Ezell, Max Kaufmann, Kevin Wei, Lewis Hammond, Herbie Bradley, Emma Bluemke, Nitarshan Rajkumar, David Krueger, Noam Kolt, Lennart Heim, Markus Anderljung
Visibility into AI Agents. FAccT (2024)
Alan Chan, Noam Kolt, Peter Wills, Usman Anwar, Christian Schröder de Witt, Nitarshan Rajkumar, Lewis Hammond, David Krueger, Lennart Heim, Markus Anderljung
IDs for AI Systems. CoRR (2024)
Alan Chan, Carson Ezell, Max Kaufmann, Kevin Wei, Lewis Hammond, Herbie Bradley, Emma Bluemke, Nitarshan Rajkumar, David Krueger, Noam Kolt, Lennart Heim, Markus Anderljung
Visibility into AI Agents. CoRR (2024)
Anka Reuel, Ben Bucknall, Stephen Casper, Tim 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
Open Problems in Technical AI Governance. CoRR (2024)
Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj
Harms from Increasingly Agentic Algorithmic Systems. FAccT (2023)
Alan Chan, Herbie Bradley, Nitarshan Rajkumar
Reclaiming the Digital Commons: A Public Data Trust for Training Data. AIES (2023)
Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, Sara Hooker
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics. ICLR (2023)
Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj
Harms from Increasingly Agentic Algorithmic Systems. CoRR (2023)
Alan Chan, Herbie Bradley, Nitarshan Rajkumar
Reclaiming the Digital Commons: A Public Data Trust for Training Data. CoRR (2023)
Nikolaus H. R. Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon
Myriad: a real-world testbed to bridge trajectory optimization and deep learning. NeurIPS (2022)
Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, Sara Hooker
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics. CoRR (2022)
Nitarshan Rajkumar, Raymond Li, Dzmitry Bahdanau
Evaluating the Text-to-SQL Capabilities of Large Language Models. CoRR (2022)
Nikolaus H. R. Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon
Myriad: a real-world testbed to bridge trajectory optimization and deep learning. CoRR (2022)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. CoRR (2021)
Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R. Devon Hjelm, Philip Bachman, Aaron C. Courville
Pretraining Representations for Data-Efficient Reinforcement Learning. NeurIPS (2021)
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy
In search of robust measures of generalization. NeurIPS (2020)
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy
In Search of Robust Measures of Generalization. CoRR (2020)
Bryan M. Li, Alexander Imani Cowen-Rivers, Piotr Kozakowski, David Tao, Siddhartha Kamalakara, Nitarshan Rajkumar, Hariharan Sezhiyan, Sicong Huang, Aidan N. Gomez
RL: Generic reinforcement learning codebase in TensorFlow. J. Open Source Softw. 4 (42) (2019)