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2020 – today
- 2024
[c10]Marwa Abdulhai, Micah Carroll, Justin Svegliato, Anca D. Dragan, Sergey Levine:
Defining Deception in Decision Making. AAMAS 2024: 2111-2113- [c9]Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan:
AI Alignment with Changing and Influenceable Reward Functions. ICML 2024 - [i14]Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan:
AI Alignment with Changing and Influenceable Reward Functions. CoRR abs/2405.17713 (2024) - [i13]Tan Zhi-Xuan, Micah Carroll, Matija Franklin, Hal Ashton:
Beyond Preferences in AI Alignment. CoRR abs/2408.16984 (2024) - 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) - [c8]Micah Carroll
, Alan Chan, Henry Ashton, David Krueger:
Characterizing Manipulation from AI Systems. EAAMO 2023: 6:1-6:13 - [c7]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 M. 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: 651-666 - [c6]Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael D. Dennis, Stuart Russell:
Who Needs to Know? Minimal Knowledge for Optimal Coordination. ICML 2023: 18599-18613 - [i12]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 M. 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 abs/2302.10329 (2023) - [i11]Micah Carroll, Alan Chan, Henry Ashton, David Krueger:
Characterizing Manipulation from AI Systems. CoRR abs/2303.09387 (2023) - [i10]Smitha Milli, Micah Carroll, Sashrika Pandey, Yike Wang, Anca D. Dragan:
Twitter's Algorithm: Amplifying Anger, Animosity, and Affective Polarization. CoRR abs/2305.16941 (2023) - [i9]Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael Dennis, Stuart Russell:
Who Needs to Know? Minimal Knowledge for Optimal Coordination. CoRR abs/2306.09309 (2023) - [i8]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
- [c5]Micah D. Carroll, Anca D. Dragan, Stuart Russell, Dylan Hadfield-Menell:
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. ICML 2022: 2686-2708 - [c4]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS 2022 - [i7]Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. CoRR abs/2204.11966 (2022) - [i6]Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR abs/2204.13326 (2022) - [i5]Mesut Yang, Micah Carroll, Anca D. Dragan:
Optimal Behavior Prior: Data-Efficient Human Models for Improved Human-AI Collaboration. CoRR abs/2211.01602 (2022) - [i4]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
UniMASK: Unified Inference in Sequential Decision Problems. CoRR abs/2211.10869 (2022) - [i3]David Zhang, Micah Carroll, Andreea Bobu, Anca D. Dragan:
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking. CoRR abs/2212.00169 (2022) - 2021
- [c3]Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah:
Evaluating the Robustness of Collaborative Agents. AAMAS 2021: 1560-1562 - [c2]Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
Estimating and Penalizing Preference Shift in Recommender Systems. RecSys 2021: 661-667 - [i2]Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah:
Evaluating the Robustness of Collaborative Agents. CoRR abs/2101.05507 (2021)
2010 – 2019
- 2019
- [c1]Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan:
On the Utility of Learning about Humans for Human-AI Coordination. NeurIPS 2019: 5175-5186 - [i1]Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan:
On the Utility of Learning about Humans for Human-AI Coordination. CoRR abs/1910.05789 (2019)
Coauthor Index
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last updated on 2024-09-30 00:08 CEST by the dblp team
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