Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale. - Scott Emmons; Stephen G. Kobourov; Mike Gallant; Katy Börner (CoRR, 2016)

Post-Processing Partitions to Identify Domains of Modularity Optimization. - William H. Weir; Scott Emmons; Ryan Gibson; Dane Taylor; Peter J. Mucha (Algorithms, 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)

A Map Equation with Metadata: Varying the Role of Attributes in Community Detection. - Scott Emmons; Peter J. Mucha (CoRR, 2018)

Global Redundancy Resolution via Continuous Pseudoinversion of the Forward Kinematic Map. - Kris Hauser; Scott Emmons (IEEE Trans Autom. Sci. Eng., 2018)

Sparse Graphical Memory for Robust Planning. - Scott Emmons; Ajay Jain; Michael Laskin; Thanard Kurutach; Pieter Abbeel; Deepak Pathak (NeurIPS, 2020)

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 001; Pieter Abbeel; et al. (NeurIPS Datasets and Benchmarks, 2021)

RvS: What is Essential for Offline RL via Supervised Learning? - Scott Emmons; Benjamin Eysenbach; Ilya Kostrikov; Sergey Levine (ICLR, 2022)

For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria. - Scott Emmons; Caspar Oesterheld; Andrew Critch; Vincent Conitzer; Stuart Russell 001 (ICML, 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 001; Pieter Abbeel; Rohin Shah (CoRR, 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 001 (CoRR, 2022)

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 002; Scott Emmons; Dan Hendrycks (ICML, 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 002; Scott Emmons; Dan Hendrycks (CoRR, 2023)

ALMANACS: A Simulatability Benchmark for Language Model Explainability. - Edmund Mills; Shiye Su; Stuart Russell 001; Scott Emmons (CoRR, 2023)

Image Hijacks: Adversarial Images can Control Generative Models at Runtime. - Luke Bailey; Euan Ong; Stuart Russell 001; Scott Emmons (ICML, 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 (NeurIPS, 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 (NeurIPS, 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 (NeurIPS, 2024)

Uncovering Latent Human Wellbeing in Language Model Embeddings. - Pedro Freire; ChengCheng Tan; Adam Gleave; Dan Hendrycks; Scott Emmons (CoRR, 2024)

When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning. - Leon Lang; Davis Foote; Stuart Russell 001; Anca D. Dragan; Erik Jenner; 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; et al. (CoRR, 2024)

Will an AI with Private Information Allow Itself to Be Switched Off? - Andrew Garber; Rohan Subramani; Linus Luu; Mark Bedaywi; Stuart Russell 001; Scott Emmons (CoRR, 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)

Observation Interference in Partially Observable Assistance Games. - Scott Emmons; Caspar Oesterheld; Vincent Conitzer; Stuart Russell 001 (CoRR, 2024)

The Alignment Problem Under Partial Observability - Scott Emmons (2024)

The Partially Observable Off-Switch Game. - Andrew Garber; Rohan Subramani; Linus Luu; Mark Bedaywi; Stuart Russell 001; Scott Emmons (AAAI, 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; et al. (ICLR, 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; et al. (CoRR, 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, 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 003; Alan Cooney; Allan Dafoe; Anca D. Dragan; Scott Emmons; Owain Evans; et al. (CoRR, 2025)