Dylan Hadfield-Menell

According to our database, Dylan Hadfield-Menell authored at least 58 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Defending Against Unforeseen Failure Modes with Latent Adversarial Training.

Stephen Casper, Lennart Schulze, Oam Patel, Dylan Hadfield-Menell

CoRR, 2024

Eight Methods to Evaluate Robust Unlearning in LLMs.

Aengus Lynch, Phillip Guo, Aidan Ewart, Stephen Casper, Dylan Hadfield-Menell

CoRR, 2024

Black-Box Access is Insufficient for Rigorous AI Audits.

Stephen Casper, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas Alexander Haupt, Kevin Wei, Jérémy Scheurer, Marius Hobbhahn, Lee Sharkey, Satyapriya Krishna, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell

CoRR, 2024

2023

Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF.

Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell

CoRR, 2023

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony 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

CoRR, 2023

Measuring the Success of Diffusion Models at Imitating Human Artists.

Stephen Casper, Zifan Guo, Shreya Mogulothu, Zachary Marinov, Chinmay Deshpande, Rui-Jie Yew, Zheng Dai, Dylan Hadfield-Menell

CoRR, 2023

Explore, Establish, Exploit: Red Teaming Language Models from Scratch.

Stephen Casper, Jason Lin, Joe Kwon, Gatlen Culp, Dylan Hadfield-Menell

CoRR, 2023

Benchmarking Interpretability Tools for Deep Neural Networks.

Stephen Casper, Yuxiao Li, Jiawei Li, Tong Bu, Kevin Zhang, Dylan Hadfield-Menell

CoRR, 2023

Recommending to Strategic Users.

Andreas A. Haupt, Dylan Hadfield-Menell, Chara Podimata

CoRR, 2023

Red Teaming Deep Neural Networks with Feature Synthesis Tools.

Stephen Casper, Tong Bu, Yuxiao Li, Jiawei Li, Kevin Zhang, Kaivalya Hariharan, Dylan Hadfield-Menell

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?

Kevin Liu, Stephen Casper, Dylan Hadfield-Menell, Jacob Andreas

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Get It in Writing: Formal Contracts Mitigate Social Dilemmas in Multi-Agent RL.

Phillip J. K. Christoffersen, Andreas A. Haupt, Dylan Hadfield-Menell

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

White-Box Adversarial Policies in Deep Reinforcement Learning.

Stephen Casper, Dylan Hadfield-Menell, Gabriel Kreiman

Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023) co-located with the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2023

2022

Diagnostics for Deep Neural Networks with Automated Copy/Paste Attacks.

Stephen Casper, Kaivalya Hariharan, Dylan Hadfield-Menell

CoRR, 2022

Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks.

Tilman Räuker, Anson Ho, Stephen Casper, Dylan Hadfield-Menell

CoRR, 2022

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis.

Jonathan Stray, Alon Y. Halevy, Parisa Assar, Dylan Hadfield-Menell, Craig Boutilier, Amar Ashar, Lex Beattie, Michael D. Ekstrand, Claire Leibowicz, Connie Moon Sehat, Sara Johansen, Lianne Kerlin, David Vickrey, Spandana Singh, Sanne Vrijenhoek, Amy X. Zhang, McKane Andrus, Natali Helberger, Polina Proutskova, Tanushree Mitra, Nina Vasan

CoRR, 2022

How to talk so your robot will learn: Instructions, descriptions, and pragmatics.

Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Thomas L. Griffiths, Dylan Hadfield-Menell

CoRR, 2022

Linguistic communication as (inverse) reward design.

Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Thomas L. Griffiths, Dylan Hadfield-Menell

CoRR, 2022

Towards Psychologically-Grounded Dynamic Preference Models.

Mihaela Curmei, Andreas A. Haupt, Benjamin Recht, Dylan Hadfield-Menell

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

How to talk so AI will learn: Instructions, descriptions, and autonomy.

Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Tom Griffiths, Dylan Hadfield-Menell

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Feature-Level Adversaries are Interpretability Tools.

Stephen Casper, Max Nadeau, Dylan Hadfield-Menell, Gabriel Kreiman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Estimating and Penalizing Induced Preference Shifts in Recommender Systems.

Micah D. Carroll, Anca D. Dragan, Stuart Russell, Dylan Hadfield-Menell

Proceedings of the International Conference on Machine Learning, 2022

A Penalty Default Approach to Preemptive Harm Disclosure and Mitigation for AI Systems.

Rui-Jie Yew, Dylan Hadfield-Menell

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

When Curation Becomes Creation: Algorithms, microcontent, and the vanishing distinction between platforms and creators.

Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton

ACM Queue, 2021

What are you optimizing for? Aligning Recommender Systems with Human Values.

Jonathan Stray, Ivan Vendrov, Jeremy Nixon, Steven Adler, Dylan Hadfield-Menell

CoRR, 2021

When curation becomes creation.

Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton

Commun. ACM, 2021

Estimating and Penalizing Preference Shift in Recommender Systems.

Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Guided Imitation of Task and Motion Planning.

Michael James McDonald, Dylan Hadfield-Menell

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

Multi-Principal Assistance Games: Definition and Collegial Mechanisms.

Arnaud Fickinger, Simon Zhuang, Andrew Critch, Dylan Hadfield-Menell, Stuart Russell

CoRR, 2020

Multi-Principal Assistance Games.

Arnaud Fickinger, Simon Zhuang, Dylan Hadfield-Menell, Stuart Russell

CoRR, 2020

Consequences of Misaligned AI.

Simon Zhuang, Dylan Hadfield-Menell

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Silly Rules Improve the Capacity of Agents to Learn Stable Enforcement and Compliance Behaviors.

Raphael Koster, Dylan Hadfield-Menell, Gillian K. Hadfield, Joel Z. Leibo

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Conservative Agency via Attainable Utility Preservation.

Alexander Matt Turner, Dylan Hadfield-Menell, Prasad Tadepalli

Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

2019

An Extensible Interactive Interface for Agent Design.

Matthew Rahtz, James Fang, Anca D. Dragan, Dylan Hadfield-Menell

CoRR, 2019

Adversarial Training with Voronoi Constraints.

Marc Khoury, Dylan Hadfield-Menell

CoRR, 2019

Conservative Agency.

Alexander Matt Turner, Dylan Hadfield-Menell, Prasad Tadepalli

Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the 28th International Joint Conference on Artificial Intelligence, 2019

On the Utility of Model Learning in HRI.

Rohan Choudhury, Gokul Swamy, Dylan Hadfield-Menell, Anca D. Dragan

Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, 2019

The Assistive Multi-Armed Bandit.

Lawrence Chan, Dylan Hadfield-Menell, Siddhartha S. Srinivasa, Anca D. Dragan

Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, 2019

Human-AI Learning Performance in Multi-Armed Bandits.

Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Incomplete Contracting and AI Alignment.

Dylan Hadfield-Menell, Gillian K. Hadfield

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Legible Normativity for AI Alignment: The Value of Silly Rules.

Dylan Hadfield-Menell, McKane Andrus, Gillian K. Hadfield

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018

On the Geometry of Adversarial Examples.

Marc Khoury, Dylan Hadfield-Menell

CoRR, 2018

Active Inverse Reward Design.

Sören Mindermann, Rohin Shah, Adam Gleave, Dylan Hadfield-Menell

CoRR, 2018

Simplifying Reward Design through Divide-and-Conquer.

Ellis Ratner, Dylan Hadfield-Menell, Anca D. Dragan

Proceedings of the Robotics: Science and Systems XIV, 2018

An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning.

Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Inverse Reward Design.

Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart J. Russell, Anca D. Dragan

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Pragmatic-Pedagogic Value Alignment.

Jaime F. Fisac, Monica A. Gates, Jessica B. Hamrick, Chang Liu, Dylan Hadfield-Menell, Malayandi Palaniappan, Dhruv Malik, S. Shankar Sastry, Thomas L. Griffiths, Anca D. Dragan

Proceedings of the Robotics Research, The 18th International Symposium, 2017

Should Robots be Obedient?

Smitha Milli, Dylan Hadfield-Menell, Anca D. Dragan, Stuart Russell

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Expressive Robot Motion Timing.

Allan Zhou, Dylan Hadfield-Menell, Anusha Nagabandi, Anca D. Dragan

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 2017

The Off-Switch Game.

Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell

Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Cooperative Inverse Reinforcement Learning.

Dylan Hadfield-Menell, Stuart Russell, Pieter Abbeel, Anca D. Dragan

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Sequential quadratic programming for task plan optimization.

Dylan Hadfield-Menell, Christopher Lin, Rohan Chitnis, Stuart Russell, Pieter Abbeel

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Guided search for task and motion plans using learned heuristics.

Rohan Chitnis, Dylan Hadfield-Menell, Abhishek Gupta, Siddharth Srivastava, Edward Groshev, Christopher Lin, Pieter Abbeel

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015

Multitasking: Optimal Planning for Bandit Superprocesses.

Dylan Hadfield-Menell, Stuart Russell

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Modular task and motion planning in belief space.

Dylan Hadfield-Menell, Edward Groshev, Rohan Chitnis, Pieter Abbeel

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Beyond lowest-warping cost action selection in trajectory transfer.

Dylan Hadfield-Menell, Alex X. Lee, Chelsea Finn, Eric Tzeng, Sandy H. Huang, Pieter Abbeel

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Unifying scene registration and trajectory optimization for learning from demonstrations with application to manipulation of deformable objects.

Alex X. Lee, Sandy H. Huang, Dylan Hadfield-Menell, Eric Tzeng, Pieter Abbeel

Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

2013

Optimization in the now: Dynamic peephole optimization for hierarchical planning.

Dylan Hadfield-Menell, Leslie Pack Kaelbling, Tomás Lozano-Pérez

Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013