Tom Tseng

According to our database, Tom Tseng authored at least 14 papers between 2019 and 2026.

Collaborative distances:

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

2026

Concept Influence: Leveraging Interpretability to Improve Performance and Efficiency in Training Data Attribution.

Matthew Kowal, Goncalo Paulo, Louis Jaburi, Tom Tseng, Lev E. McKinney, Stefan Heimersheim, Aaron David Tucker, Adam Gleave, Kellin Pelrine

CoRR, February, 2026

TamperBench: Systematically Stress-Testing LLM Safety Under Fine-Tuning and Tampering.

Saad Hossain, Tom Tseng, Punya Syon Pandey, Samanvay Vajpayee, Matthew Kowal, Nayeema Nonta, Samuel Simko, Stephen Casper, Zhijing Jin, Kellin Pelrine, Sirisha Rambhatla

CoRR, February, 2026

STACK: Adversarial Attacks on LLM Safeguard Pipelines.

Ian R. McKenzie, Oskar John Hollinsworth, Tom Tseng, Xander Davies, Stephen Casper, Aaron David Tucker, Robert Kirk, Adam Gleave

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Scaling Trends in Language Model Robustness.

Nikolaus H. R. Howe, Ian R. McKenzie, Oskar John Hollinsworth, Michal Zajac, Tom Tseng, Aaron David Tucker, Pierre-Luc Bacon, Adam Gleave

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

Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility.

Brendan Murphy, Dillon Bowen, Shahrad Mohammadzadeh, Tom Tseng, Julius Broomfield, Adam Gleave, Kellin Pelrine

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Can Go AIs Be Adversarially Robust?

Tom Tseng, Euan McLean, Kellin Pelrine, Tony Tong Wang, Adam Gleave

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

2024

Exploring Scaling Trends in LLM Robustness.

Nikolaus H. R. Howe, Michal Zajac, Ian R. McKenzie, Oskar John Hollinsworth, Tom Tseng, Pierre-Luc Bacon, Adam Gleave

CoRR, 2024

2023

Inverse Scaling: When Bigger Isn't Better.

Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, Ethan Perez

Trans. Mach. Learn. Res., 2023

Adversarial Policies Beat Superhuman Go AIs.

Tony Tong Wang, Adam Gleave, Tom Tseng, Kellin Pelrine, Nora Belrose, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell

Proceedings of the International Conference on Machine Learning, 2023

2022

Adversarial Policies Beat Professional-Level Go AIs.

Tony Tong Wang, Adam Gleave, Nora Belrose, Tom Tseng, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell

CoRR, 2022

Parallel Batch-Dynamic Minimum Spanning Forest and the Efficiency of Dynamic Agglomerative Graph Clustering.

Tom Tseng, Laxman Dhulipala, Julian Shun

Proceedings of the SPAA '22: 34th ACM Symposium on Parallelism in Algorithms and Architectures, Philadelphia, PA, USA, July 11, 2022

2021

Parallel Index-Based Structural Graph Clustering and Its Approximation.

Tom Tseng, Laxman Dhulipala, Julian Shun

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

2020

The Graph Based Benchmark Suite (GBBS).

Laxman Dhulipala, Jessica Shi, Tom Tseng, Guy E. Blelloch, Julian Shun

Proceedings of the GRADES-NDA'20: Proceedings of the 3rd Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), 2020

2019

Batch-Parallel Euler Tour Trees.

Thomas Tseng, Laxman Dhulipala, Guy E. Blelloch

Proceedings of the Twenty-First Workshop on Algorithm Engineering and Experiments, 2019