Aengus Lynch

According to our database, Aengus Lynch authored at least 13 papers between 2023 and 2026.

Collaborative distances:

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

2026

An Independent Safety Evaluation of Kimi K2.5.

Zheng-Xin Yong, Parv Mahajan, Andy Wang, Ida Caspary, Yernat Yestekov, Zora Che, Mosh Levy, Elle Najt, Dennis Murphy, Prashant Kulkarni, Lev McKinney, Kei Nishimura-Gasparian, Ram Potham, Aengus Lynch, Michael L. Chen

CoRR, April, 2026

The Persistent Vulnerability of Aligned AI Systems.

Aengus Lynch

CoRR, April, 2026

2025

Agentic Misalignment: How LLMs Could Be Insider Threats.

Aengus Lynch, Benjamin Wright, Caleb Larson, Stuart J. Ritchie, Sören Mindermann, Evan Hubinger, Ethan Perez, Kevin K. Troy

CoRR, October, 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

Causal Machine Learning: A Survey and Open Problems.

Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva

Found. Trends Optim., 2025

How Do Large Language Monkeys Get Their Power (Laws)?

Rylan Schaeffer, Joshua Kazdan, John Hughes, Jordan Juravsky, Sara Price, Aengus Lynch, Erik Jones, Robert Kirk, Azalia Mirhoseini, Sanmi Koyejo

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

2024

Best-of-N Jailbreaking.

John Hughes, Sara Price, Aengus Lynch, Rylan Schaeffer, Fazl Barez, Sanmi Koyejo, Henry Sleight, Erik Jones, Ethan Perez, Mrinank Sharma

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

Analyzing the Generalization and Reliability of Steering Vectors.

Daniel Tan, David Chanin, Aengus Lynch, Dimitrios Kanoulas, Brooks Paige, Adrià Garriga-Alonso, Robert Kirk

CoRR, 2024

Eight Methods to Evaluate Robust Unlearning in LLMs.

Aengus Lynch, Phillip Guo, Aidan Ewart, Stephen Casper, Dylan Hadfield-Menell

CoRR, 2024

Analysing the Generalisation and Reliability of Steering Vectors.

Daniel Tan, David Chanin, Aengus Lynch, Brooks Paige, Dimitrios Kanoulas, Adrià Garriga-Alonso, Robert Kirk

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases.

Aengus Lynch, Gbètondji J.-S. Dovonon, Jean Kaddour, Ricardo Silva

CoRR, 2023

Towards Automated Circuit Discovery for Mechanistic Interpretability.

Arthur Conmy, Augustine N. Mavor-Parker, Aengus Lynch, Stefan Heimersheim, Adrià Garriga-Alonso

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023