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2020 – today
- 2025
[j3]Zora Che, Stephen Casper, Robert Kirk, Anirudh Satheesh, Stewart Slocum, Lev E. McKinney, Rohit Gandikota, Aidan Ewart, Domenic Rosati, Zichu Wu, Zikui Cai, Bilal Chughtai, Yarin Gal, Furong Huang, Dylan Hadfield-Menell:
Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities. Trans. Mach. Learn. Res. 2025 (2025)- [c1]Stewart Slocum, Asher Parker-Sartori, Dylan Hadfield-Menell:
Diverse Preference Learning for Capabilities and Alignment. ICLR 2025 - [i9]Stephen Casper, Luke Bailey, Rosco Hunter, Carson Ezell, Emma Cabalé, Michael Gerovitch, Stewart Slocum, Kevin Wei
, Nikola Jurkovic, Ariba Khan, Phillip J. K. Christoffersen, A. Pinar Ozisik, Rakshit S. Trivedi, Dylan Hadfield-Menell, Noam Kolt:
The AI Agent Index. CoRR abs/2502.01635 (2025) - [i8]Zora Che, Stephen Casper, Robert Kirk, Anirudh Satheesh, Stewart Slocum, Lev E. McKinney, Rohit Gandikota, Aidan Ewart, Domenic Rosati, Zichu Wu, Zikui Cai, Bilal Chughtai, Yarin Gal, Furong Huang, Dylan Hadfield-Menell:
Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities. CoRR abs/2502.05209 (2025) - [i7]Mehul Damani, Isha Puri, Stewart Slocum, Idan Shenfeld, Leshem Choshen, Yoon Kim, Jacob Andreas:
Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty. CoRR abs/2507.16806 (2025) - [i6]Julian Minder, Clément Dumas, Stewart Slocum, Helena Casademunt, Cameron Holmes, Robert West, Neel Nanda:
Narrow Finetuning Leaves Clearly Readable Traces in Activation Differences. CoRR abs/2510.13900 (2025) - [i5]Stewart Slocum, Julian Minder, Clément Dumas, Henry Sleight, Ryan Greenblatt, Samuel Marks, Rowan Wang:
Believe It or Not: How Deeply do LLMs Believe Implanted Facts? CoRR abs/2510.17941 (2025) - [i4]Stewart Slocum, Asher Parker-Sartori, Dylan Hadfield-Menell:
Diverse Preference Learning for Capabilities and Alignment. CoRR abs/2511.08594 (2025) - 2023
- [j2]Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman:
Interpretable by Design: Learning Predictors by Composing Interpretable Queries. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7430-7443 (2023) - [j1]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. 2023 (2023) - [i3]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. CoRR abs/2307.15217 (2023) - 2022
- [i2]Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman:
Interpretable by Design: Learning Predictors by Composing Interpretable Queries. CoRR abs/2207.00938 (2022) - 2020
- [i1]Sam Sinai, Richard Wang, Alexander Whatley, Stewart Slocum, Elina Locane, Eric D. Kelsic:
AdaLead: A simple and robust adaptive greedy search algorithm for sequence design. CoRR abs/2010.02141 (2020)
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