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ORCIDTony T. Wang 0001
Person information
- affiliation: MIT, CSAIL, Cambridge, MA, USA
Other persons with the same name
- Tony T. Wang 0002 — Food and Drug Administration, Silver Spring, MD, USA
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Journal Articles
- 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)
Conference and Workshop Papers
- 2024
- [c2]Danny Halawi, Alexander Wei, Eric Wallace, Tony Tong Wang, Nika Haghtalab, Jacob Steinhardt:
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. ICML 2024 - 2023
- [c1]Tony Tong Wang, Adam Gleave, Tom Tseng
, Kellin Pelrine, Nora Belrose, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell:
Adversarial Policies Beat Superhuman Go AIs. ICML 2023: 35655-35739
Informal and Other Publications
- 2024
- [i6]Tom Tseng, Euan McLean, Kellin Pelrine, Tony T. Wang, Adam Gleave:
Can Go AIs be adversarially robust? CoRR abs/2406.12843 (2024) - [i5]Danny Halawi, Alexander Wei, Eric Wallace, Tony T. Wang, Nika Haghtalab, Jacob Steinhardt:
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation. CoRR abs/2406.20053 (2024) - 2023
- [i4]Tony T. Wang, Igor Zablotchi, Nir Shavit, Jonathan S. Rosenfeld:
Cliff-Learning. CoRR abs/2302.07348 (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) - [i2]Tony T. Wang, Miles Wang, Kaivalya Hariharan, Nir Shavit:
Forbidden Facts: An Investigation of Competing Objectives in Llama-2. CoRR abs/2312.08793 (2023) - 2022
- [i1]Tony Tong Wang, Adam Gleave, Nora Belrose, Tom Tseng, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell:
Adversarial Policies Beat Professional-Level Go AIs. CoRR abs/2211.00241 (2022)
Coauthor Index
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