Bilal Chughtai

According to our database, Bilal Chughtai authored at least 15 papers between 2018 and 2026.

Collaborative distances:

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

2026

Training on Documents About Monitoring Leads to CoT Obfuscation.

Reilly Haskins, Bilal Chughtai, Joshua Engels

CoRR, May, 2026

Building Production-Ready Probes For Gemini.

János Kramár, Joshua Engels, Zheng Wang, Bilal Chughtai, Rohin Shah, Neel Nanda, Arthur Conmy

CoRR, January, 2026

2025

Difficulties with Evaluating a Deception Detector for AIs.

Lewis Smith, Bilal Chughtai, Neel Nanda

CoRR, November, 2025

Detecting Strategic Deception Using Linear Probes.

Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim, Marius Hobbhahn

CoRR, February, 2025

Open Problems in Mechanistic Interpretability.

Lee Sharkey, Bilal Chughtai, Joshua Batson, Jack Lindsey, Jeffrey Wu, Lucius Bushnaq, Nicholas Goldowsky-Dill, Stefan Heimersheim, Alejandro Ortega, Joseph Isaac Bloom, Stella Biderman, Adrià Garriga-Alonso, Arthur Conmy, Neel Nanda, Jessica Rumbelow, Martin Wattenberg, Nandi Schoots, Joseph Miller, William Saunders, Eric J. Michaud, Stephen Casper, Max Tegmark, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, Tom McGrath

Trans. Mach. Learn. Res., 2025

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities.

Zora Che, Stephen Casper, Robert Kirk, Anirudh Satheesh, Stewart Slocum, Lev E. McKinney, Rohit Gandikota, Aidan Ewart, Domenic Rosati, Zichu Wu, Zikui Cai, Bilal Chughtai, Yarin Gal, Furong Huang, Dylan Hadfield-Menell

Trans. Mach. Learn. Res., 2025

Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning.

Julian Minder, Clément Dumas, Caden Juang, Bilal Chughtai, Neel Nanda

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Detecting Strategic Deception with Linear Probes.

Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim, Marius Hobbhahn

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

2024

Towards evaluations-based safety cases for AI scheming.

Mikita Balesni, Marius Hobbhahn, David Lindner, Alexander Meinke, Tomek Korbak, Joshua Clymer, Buck Shlegeris, Jérémy Scheurer, Charlotte Stix, Rusheb Shah, Nicholas Goldowsky-Dill, Dan Braun, Bilal Chughtai, Owain Evans, Daniel Kokotajlo, Lucius Bushnaq

CoRR, 2024

Transformer Circuit Faithfulness Metrics are not Robust.

Joseph Miller, Bilal Chughtai, William Saunders

CoRR, 2024

Can Language Models Explain Their Own Classification Behavior?

Dane Sherburn, Bilal Chughtai, Owain Evans

CoRR, 2024

Summing Up the Facts: Additive Mechanisms Behind Factual Recall in LLMs.

Bilal Chughtai, Alan Cooney, Neel Nanda

CoRR, 2024

Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs.

Rudolf Laine, Bilal Chughtai, Jan Betley, Kaivalya Hariharan, Mikita Balesni, Jérémy Scheurer, Marius Hobbhahn, Alexander Meinke, Owain Evans

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

2023

A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations.

Bilal Chughtai, Lawrence Chan, Neel Nanda

Proceedings of the International Conference on Machine Learning, 2023

2018

Variable Selection for Chronic Disease Outcome Prediction Using a Causal Inference Technique: A Preliminary Study.

John Richard Lee, Bilal Chughtai, Rema Padman

Proceedings of the IEEE International Conference on Healthcare Informatics, 2018