Scott Emmons

According to our database, Scott Emmons authored at least 18 papers between 2016 and 2024.

Collaborative distances:

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

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

CoRR, 2024

2023

ALMANACS: A Simulatability Benchmark for Language Model Explainability.

Edmund Mills, Shiye Su, Stuart Russell, Scott Emmons

CoRR, 2023

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

Luke Bailey, Euan Ong, 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