Optimization in the now: Dynamic peephole optimization for hierarchical planning. - Dylan Hadfield-Menell; Leslie Pack Kaelbling; Tomás Lozano-Pérez (ICRA, 2013)

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 (IROS, 2014)

Beyond lowest-warping cost action selection in trajectory transfer. - Dylan Hadfield-Menell; Alex X. Lee; Chelsea Finn; Eric Tzeng; Sandy H. Huang; Pieter Abbeel (ICRA, 2015)

Modular task and motion planning in belief space. - Dylan Hadfield-Menell; Edward Groshev; Rohan Chitnis; Pieter Abbeel (IROS, 2015)

Multitasking: Optimal Planning for Bandit Superprocesses. - Dylan Hadfield-Menell; Stuart Russell 001 (UAI, 2015)

Guided search for task and motion plans using learned heuristics. - Rohan Chitnis; Dylan Hadfield-Menell; Abhishek Gupta 004; Siddharth Srivastava 001; Edward Groshev; Christopher Lin; Pieter Abbeel (ICRA, 2016)

Sequential quadratic programming for task plan optimization. - Dylan Hadfield-Menell; Christopher Lin; Rohan Chitnis; Stuart Russell 001; Pieter Abbeel (IROS, 2016)

Cooperative Inverse Reinforcement Learning. - Dylan Hadfield-Menell; Stuart Russell 001; Pieter Abbeel; Anca D. Dragan (NIPS, 2016)

The Off-Switch Game. - Dylan Hadfield-Menell; Anca D. Dragan; Pieter Abbeel; Stuart Russell 001 (AAAI Workshops, 2017)

Expressive Robot Motion Timing. - Allan Zhou; Dylan Hadfield-Menell; Anusha Nagabandi; Anca D. Dragan (HRI, 2017)

Should Robots be Obedient? - Smitha Milli; Dylan Hadfield-Menell; Anca D. Dragan; Stuart Russell 001 (IJCAI, 2017)

Pragmatic-Pedagogic Value Alignment. - Jaime F. Fisac; Monica A. Gates; Jessica B. Hamrick; Chang Liu 002; Dylan Hadfield-Menell; Malayandi Palaniappan; Dhruv Malik; S. Shankar Sastry; Thomas L. Griffiths 001; Anca D. Dragan (ISRR, 2017)

Inverse Reward Design. - Dylan Hadfield-Menell; Smitha Milli; Pieter Abbeel; Stuart J. Russell; Anca D. Dragan (NIPS, 2017)

An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning. - Dhruv Malik; Malayandi Palaniappan; Jaime F. Fisac; Dylan Hadfield-Menell; Stuart Russell 001; Anca D. Dragan (ICML, 2018)

Simplifying Reward Design through Divide-and-Conquer. - Ellis Ratner; Dylan Hadfield-Menell; Anca D. Dragan (Robotics: Science and Systems, 2018)

Active Inverse Reward Design. - Sören Mindermann; Rohin Shah; Adam Gleave; Dylan Hadfield-Menell (CoRR, 2018)

On the Geometry of Adversarial Examples. - Marc Khoury; Dylan Hadfield-Menell (CoRR, 2018)

Legible Normativity for AI Alignment: The Value of Silly Rules. - Dylan Hadfield-Menell; McKane Andrus; Gillian K. Hadfield (AIES, 2019)

Incomplete Contracting and AI Alignment. - Dylan Hadfield-Menell; Gillian K. Hadfield (AIES, 2019)

Human-AI Learning Performance in Multi-Armed Bandits. - Ravi Pandya; Sandy H. Huang; Dylan Hadfield-Menell; Anca D. Dragan (AIES, 2019)

The Assistive Multi-Armed Bandit. - Lawrence Chan; Dylan Hadfield-Menell; Siddhartha S. Srinivasa; Anca D. Dragan (HRI, 2019)

On the Utility of Model Learning in HRI. - Rohan Choudhury; Gokul Swamy; Dylan Hadfield-Menell; Anca D. Dragan (HRI, 2019)

Conservative Agency. - Alexander Matt Turner; Dylan Hadfield-Menell; Prasad Tadepalli (AISafety@IJCAI, 2019)

Adversarial Training with Voronoi Constraints. - Marc Khoury; Dylan Hadfield-Menell (CoRR, 2019)

An Extensible Interactive Interface for Agent Design. - Matthew Rahtz; James Fang; Anca D. Dragan; Dylan Hadfield-Menell (CoRR, 2019)

Conservative Agency via Attainable Utility Preservation. - Alexander Matt Turner; Dylan Hadfield-Menell; Prasad Tadepalli (AIES, 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 (AAMAS, 2020)

Consequences of Misaligned AI. - Simon Zhuang; Dylan Hadfield-Menell (NeurIPS, 2020)

Multi-Principal Assistance Games. - Arnaud Fickinger; Simon Zhuang; Dylan Hadfield-Menell; Stuart Russell 001 (CoRR, 2020)

Multi-Principal Assistance Games: Definition and Collegial Mechanisms. - Arnaud Fickinger; Simon Zhuang; Andrew Critch; Dylan Hadfield-Menell; Stuart Russell 001 (CoRR, 2020)

Guided Imitation of Task and Motion Planning. - Michael James McDonald; Dylan Hadfield-Menell (CoRL, 2021)

Estimating and Penalizing Preference Shift in Recommender Systems. - Micah Carroll; Dylan Hadfield-Menell; Stuart Russell 001; Anca D. Dragan (RecSys, 2021)

When curation becomes creation. - Liu Leqi; Dylan Hadfield-Menell; Zachary C. Lipton (Commun. ACM, 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: Algorithms, microcontent, and the vanishing distinction between platforms and creators. - Liu Leqi; Dylan Hadfield-Menell; Zachary C. Lipton (ACM Queue, 2021)

A Penalty Default Approach to Preemptive Harm Disclosure and Mitigation for AI Systems. - Rui-Jie Yew; Dylan Hadfield-Menell (AIES, 2022)

Estimating and Penalizing Induced Preference Shifts in Recommender Systems. - Micah D. Carroll; Anca D. Dragan; Stuart Russell 001; Dylan Hadfield-Menell (ICML, 2022)

Robust Feature-Level Adversaries are Interpretability Tools. - Stephen Casper; Max Nadeau; Dylan Hadfield-Menell; Gabriel Kreiman (NeurIPS, 2022)

How to talk so AI will learn: Instructions, descriptions, and autonomy. - Theodore R. Sumers; Robert D. Hawkins; Mark K. Ho; Tom Griffiths 001; Dylan Hadfield-Menell (NeurIPS, 2022)

Towards Psychologically-Grounded Dynamic Preference Models. - Mihaela Curmei; Andreas A. Haupt; Benjamin Recht; Dylan Hadfield-Menell (RecSys, 2022)

Linguistic communication as (inverse) reward design. - Theodore R. Sumers; Robert D. Hawkins; Mark K. Ho; Thomas L. Griffiths 001; Dylan Hadfield-Menell (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 001; 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; et al. (CoRR, 2022)

Diagnostics for Deep Neural Networks with Automated Copy/Paste Attacks. - Stephen Casper; Kaivalya Hariharan; Dylan Hadfield-Menell (CoRR, 2022)

White-Box Adversarial Policies in Deep Reinforcement Learning. - Stephen Casper; Dylan Hadfield-Menell; Gabriel Kreiman (SafeAI@AAAI, 2023)

Get It in Writing: Formal Contracts Mitigate Social Dilemmas in Multi-Agent RL. - Phillip J. K. Christoffersen; Andreas A. Haupt; Dylan Hadfield-Menell (AAMAS, 2023)

Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness? - Kevin Liu; Stephen Casper; Dylan Hadfield-Menell; Jacob Andreas (EMNLP, 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 (NeurIPS, 2023)

Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks. - Tilman Räuker; Anson Ho; Stephen Casper; Dylan Hadfield-Menell (SaTML, 2023)

Recommending to Strategic Users. - Andreas A. Haupt; Dylan Hadfield-Menell; Chara Podimata (CoRR, 2023)

Benchmarking Interpretability Tools for Deep Neural Networks. - Stephen Casper; Yuxiao Li; Jiawei Li; Tong Bu; Kevin Zhang; 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)

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)

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 Tong Wang; Samuel Marks; et al. (Trans. Mach. Learn. Res., 2023)

Black-Box Access is Insufficient for Rigorous AI Audits. - Stephen Casper; Carson Ezell; Charlotte Siegmann; Noam Kolt; Taylor Lynn Curtis; Benjamin Bucknall; Andreas A. Haupt; Kevin Wei; Jérémy Scheurer; Marius Hobbhahn; Lee Sharkey; Satyapriya Krishna; et al. (FAccT, 2024)

Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. - Anand Siththaranjan; Cassidy Laidlaw; Dylan Hadfield-Menell (ICLR, 2024)

Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence. - Rakshit Trivedi; Akbir Khan; Jesse Clifton; Lewis Hammond; Edgar A. Duéñez-Guzmán; Dipam Chakraborty; John P. Agapiou; Jayd Matyas; Alexander Sasha Vezhnevets; Barna Pásztor; Yunke Ao; Omar G. Younis; et al. (NeurIPS, 2024)

Eight Methods to Evaluate Robust Unlearning in LLMs. - Aengus Lynch; Phillip Guo; Aidan Ewart; Stephen Casper; Dylan Hadfield-Menell (CoRR, 2024)

The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability. - Stephen Casper; Jieun Yun; Joonhyuk Baek; Yeseong Jung; Minhwan Kim; Kiwan Kwon; Saerom Park; Hayden Moore; David Shriver; Marissa Connor; Keltin Grimes; Angus Nicolson; et al. (CoRR, 2024)

Targeted Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs. - Abhay Sheshadri; Aidan Ewart; Phillip Guo; Aengus Lynch; Cindy Wu; Vivek Hebbar; Henry Sleight; Asa Cooper Stickland; Ethan Perez; Dylan Hadfield-Menell; Stephen Casper (CoRR, 2024)

Goal Inference from Open-Ended Dialog. - Rachel Ma; Jingyi Qu; Andreea Bobu; Dylan Hadfield-Menell (CoRR, 2024)

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis. - Jonathan Stray; Alon Y. Halevy; Parisa Assar; Dylan Hadfield-Menell; Craig Boutilier; Amar Ashar; Chloé Bakalar; Lex Beattie; Michael D. Ekstrand; Claire Leibowicz; Connie Moon Sehat; Sara Johansen; et al. (Trans. Recomm. Syst., 2024)

Formal contracts mitigate social dilemmas in multi-agent reinforcement learning. - Andreas A. Haupt; Phillip J. K. Christoffersen; Mehul Damani; Dylan Hadfield-Menell (Auton. Agents Multi Agent Syst., 2024)

Randomness, Not Representation: The Unreliability of Evaluating Cultural Alignment in LLMs. - Ariba Khan; Stephen Casper; Dylan Hadfield-Menell (FAccT, 2025)

Diverse Preference Learning for Capabilities and Alignment. - Stewart Slocum; Asher Parker-Sartori; Dylan Hadfield-Menell (ICLR, 2025)

Defending Against Unforeseen Failure Modes with Latent Adversarial Training. - Stephen Casper; Lennart Schulze; Oam Patel; Dylan Hadfield-Menell (Trans. Mach. Learn. Res., 2025)

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities. - 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; et al. (Trans. Mach. Learn. Res., 2025)

Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs. - Abhay Sheshadri; Aidan Ewart; Phillip Guo; Aengus Lynch; Cindy Wu; Vivek Hebbar; Henry Sleight; Asa Cooper Stickland; Ethan Perez; Dylan Hadfield-Menell; Stephen Casper (Trans. Mach. Learn. Res., 2025)

Disjoint Processing Mechanisms of Hierarchical and Linear Grammars in Large Language Models. - Aruna Sankaranarayanan; Dylan Hadfield-Menell; Aaron Mueller (CoRR, 2025)

The AI Agent Index. - 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; et al. (CoRR, 2025)

Pitfalls of Evidence-Based AI Policy. - Stephen Casper; David Krueger 001; Dylan Hadfield-Menell (CoRR, 2025)

Layered Unlearning for Adversarial Relearning. - Timothy Qian; Vinith Suriyakumar; Ashia Wilson; Dylan Hadfield-Menell (CoRR, 2025)

CALMA: A Process for Deriving Context-aligned Axes for Language Model Alignment. - Prajna Soni; Deepika Raman; Dylan Hadfield-Menell (CoRR, 2025)

Open-Universe Assistance Games. - Rachel Ma; Jingyi Qu; Andreea Bobu; Dylan Hadfield-Menell (CoRR, 2025)