Scott Emmons

According to our database, Scott Emmons authored at least 34 papers between 2016 and 2026.

Collaborative distances:

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

2026

Exploration Hacking: Can LLMs Learn to Resist RL Training?

Eyon Jang, Damon Falck, Joschka Braun, Nathalie Kirch, Achu Menon, Perusha Moodley, Scott Emmons, Roland S. Zimmermann, David Lindner

CoRR, April, 2026

Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies.

Miles Brundage, Noemi Dreksler, Aidan Homewood, Sean McGregor, Patricia Paskov, Conrad Stosz, Girish Sastry, A. Feder Cooper, George Balston, Steven Adler, Stephen Casper, Markus Anderljung, Grace W. Lindsay, Sören Mindermann, Vasilios Mavroudis, Ben Bucknall, Charlotte Stix, Jonas Freund, Lorenzo Pacchiardi, José Hernández-Orallo, Matteo Pistillo, Michael Chen, Chris Painter, Dean W. Ball, Cullen O'Keefe, Gabriel Weil, Ben Harack, Graeme Finley, Ryan Hassan, Scott Emmons, Charles Foster, Anka Reuel, Bri Treece, Yoshua Bengio, Daniel Reti, Rishi Bommasani, Cristian Trout, Ali Shahin Shamsabadi, Rajiv Dattani, Adrian Weller, Robert Trager, Jaime Sevilla, Lauren Wagner, Lisa Soder, Ketan Ramakrishnan, Henry Papadatos, Malcolm Murray, Ryan Tovcimak

CoRR, January, 2026

2025

Neural Chameleons: Language Models Can Learn to Hide Their Thoughts from Unseen Activation Monitors.

Max McGuinness, Alex Serrano, Luke Bailey, Scott Emmons

CoRR, December, 2025

A Pragmatic Way to Measure Chain-of-Thought Monitorability.

Scott Emmons, Roland S. Zimmermann, David K. Elson, Rohin Shah

CoRR, October, 2025

Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety.

Tomek Korbak, Mikita Balesni, Elizabeth Barnes, Yoshua Bengio, Joe Benton, Joseph Bloom, Mark Chen, Alan Cooney, Allan Dafoe, Anca D. Dragan, Scott Emmons, Owain Evans, David Farhi, Ryan Greenblatt, Dan Hendrycks, Marius Hobbhahn, Evan Hubinger, Geoffrey Irving, Erik Jenner, Daniel Kokotajlo, Victoria Krakovna, Shane Legg, David Lindner, David Luan, Aleksander Madry, Julian Michael, Neel Nanda, Dave Orr, Jakub Pachocki, Ethan Perez, Mary Phuong, Fabien Roger, Joshua Saxe, Buck Shlegeris, Martín Soto, Eric Steinberger, Jasmine Wang, Wojciech Zaremba, Bowen Baker, Rohin Shah, Vladimir Mikulik

CoRR, July, 2025

When Chain of Thought is Necessary, Language Models Struggle to Evade Monitors.

Scott Emmons, Erik Jenner, David K. Elson, Rif A. Saurous, Senthooran Rajamanoharan, Heng Chen, Irhum Shafkat, Rohin Shah

CoRR, July, 2025

An Approach to Technical AGI Safety and Security.

Rohin Shah, Alex Irpan, Alexander Matt Turner, Anna Wang, Arthur Conmy, David Lindner, Jonah Brown-Cohen, Lewis Ho, Neel Nanda, Raluca Ada Popa, Rishub Jain, Rory Greig, Samuel Albanie, Scott Emmons, Sebastian Farquhar, Sébastien Krier, Senthooran Rajamanoharan, Sophie Bridgers, Tobi Ijitoye, Tom Everitt, Victoria Krakovna, Vikrant Varma, Vladimir Mikulik, Zachary Kenton, Dave Orr, Shane Legg, Noah D. Goodman, Allan Dafoe, Four Flynn, Anca D. Dragan

CoRR, April, 2025

Observation Interference in Partially Observable Assistance Games.

Scott Emmons, Caspar Oesterheld, Vincent Conitzer, Stuart Russell

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Failures to Find Transferable Image Jailbreaks Between Vision-Language Models.

Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, Tony Tong Wang, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

The Partially Observable Off-Switch Game.

Andrew Garber, Rohan Subramani, Linus Luu, Mark Bedaywi, Stuart Russell, Scott Emmons

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

The Alignment Problem Under Partial Observability

Scott Emmons

PhD thesis, 2024

Obfuscated Activations Bypass LLM Latent-Space Defenses.

Luke Bailey, Alex Serrano, Abhay Sheshadri, Mikhail Seleznyov, Jordan Taylor, Erik Jenner, Jacob Hilton, Stephen Casper, Carlos Guestrin, Scott Emmons

CoRR, 2024

Will an AI with Private Information Allow Itself to Be Switched Off?

Andrew Garber, Rohan Subramani, Linus Luu, Mark Bedaywi, Stuart Russell, Scott Emmons

CoRR, 2024

When Do Universal Image Jailbreaks Transfer Between Vision-Language Models?

Rylan Schaeffer, Dan Valentine, Luke Bailey, James Chua, Cristóbal Eyzaguirre, Zane Durante, Joe Benton, Brando Miranda, Henry Sleight, John Hughes, Rajashree Agrawal, Mrinank Sharma, Scott Emmons, Sanmi Koyejo, Ethan Perez

CoRR, 2024

When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning.

Leon Lang, Davis Foote, Stuart Russell, Anca D. Dragan, Erik Jenner, Scott Emmons

CoRR, 2024

Uncovering Latent Human Wellbeing in Language Model Embeddings.

Pedro Freire, ChengCheng Tan, Adam Gleave, Dan Hendrycks, Scott Emmons

CoRR, 2024

A StrongREJECT for Empty Jailbreaks.

Alexandra Souly, Qingyuan Lu, Dillon Bowen, Tu Trinh, Elvis Hsieh, Sana Pandey, Pieter Abbeel, Justin Svegliato, Scott Emmons, Olivia Watkins, Sam Toyer

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback.

Leon Lang, Davis Foote, Stuart J. Russell, Anca D. Dragan, Erik Jenner, Scott Emmons

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Evidence of Learned Look-Ahead in a Chess-Playing Neural Network.

Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, Stuart J. Russell

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Image Hijacks: Adversarial Images can Control Generative Models at Runtime.

Luke Bailey, Euan Ong, Stuart Russell, Scott Emmons

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

ALMANACS: A Simulatability Benchmark for Language Model Explainability.

Edmund Mills, Shiye Su, Stuart Russell, Scott Emmons

CoRR, 2023

Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark.

Alexander Pan, Jun Shern Chan, Andy Zou, Nathaniel Li, Steven Basart, Thomas Woodside, Jonathan Ng, Hanlin Zhang, Scott Emmons, Dan Hendrycks

CoRR, 2023

Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark.

Alexander Pan, Jun Shern Chan, Andy Zou, Nathaniel Li, Steven Basart, Thomas Woodside, Hanlin Zhang, Scott Emmons, Dan Hendrycks

Proceedings of the International Conference on Machine Learning, 2023

2022

imitation: Clean Imitation Learning Implementations.

Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, Stuart Russell

CoRR, 2022

An Empirical Investigation of Representation Learning for Imitation.

Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah

CoRR, 2022

For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria.

Scott Emmons, Caspar Oesterheld, Andrew Critch, Vincent Conitzer, Stuart Russell

Proceedings of the International Conference on Machine Learning, 2022

RvS: What is Essential for Offline RL via Supervised Learning?

Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

An Empirical Investigation of Representation Learning for Imitation.

Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Sparse Graphical Memory for Robust Planning.

Scott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach, Pieter Abbeel, Deepak Pathak

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

2018

Global Redundancy Resolution via Continuous Pseudoinversion of the Forward Kinematic Map.

Kris Hauser, Scott Emmons

IEEE Trans Autom. Sci. Eng., 2018

A Map Equation with Metadata: Varying the Role of Attributes in Community Detection.

Scott Emmons, Peter J. Mucha

CoRR, 2018

2017

MOOC visual analytics: Empowering students, teachers, researchers, and platform developers of massively open online courses.

Scott Emmons, Robert P. Light, Katy Börner

J. Assoc. Inf. Sci. Technol., 2017

Post-Processing Partitions to Identify Domains of Modularity Optimization.

William H. Weir, Scott Emmons, Ryan Gibson, Dane Taylor, Peter J. Mucha

Algorithms, 2017

2016

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.

Scott Emmons, Stephen G. Kobourov, Mike Gallant, Katy Börner

CoRR, 2016