Jacob Pfau

15 papers A* 1Journal 12Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
An alignment safety case sketch based on debate.
CoRR
Marie Davidsen Buhl, Jacob Pfau, Benjamin Hilton, Geoffrey Irving
2025 — conf
When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback.
ACL (Findings)
Jane Pan, Ryan Shar, Jacob Pfau, Ameet Talwalkar, He He, Valerie Chen
2025 J jnl
When Benchmarks Talk: Re-Evaluating Code LLMs with Interactive Feedback.
CoRR
Jane Pan, Ryan Shar, Jacob Pfau, Ameet Talwalkar, He He, Valerie Chen
2024 J jnl
Let's Think Dot by Dot: Hidden Computation in Transformer Language Models.
CoRR
Jacob Pfau, William Merrill, Samuel R. Bowman
2024 J jnl
Steering Without Side Effects: Improving Post-Deployment Control of Language Models.
CoRR
Asa Cooper Stickland, Alexander Lyzhov, Jacob Pfau, Salsabila Mahdi, Samuel R. Bowman
2024 J jnl
Taking AI Welfare Seriously.
CoRR
Robert Long, Jeff Sebo, Patrick Butlin, Kathleen Finlinson, Kyle Fish, Jacqueline Harding, Jacob Pfau, Toni Sims, Jonathan Birch, David Chalmers
2023 J jnl
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.
CoRR
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
2023 J jnl
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.
Trans. Mach. Learn. Res.
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell
2023 — conf
Self-Consistency of Large Language Models under Ambiguity.
BlackboxNLP@EMNLP
Henning Bartsch, Ole Jorgensen, Domenic Rosati, Jason Hoelscher-Obermaier, Jacob Pfau
2023 J jnl
Self-Consistency of Large Language Models under Ambiguity.
CoRR
Henning Bartsch, Ole Jorgensen, Domenic Rosati, Jason Hoelscher-Obermaier, Jacob Pfau
2022 A* conf
Goal Misgeneralization in Deep Reinforcement Learning.
ICML
Lauro Langosco di Langosco, Jack Koch, Lee D. Sharkey, Jacob Pfau, David Krueger
2021 J jnl
Objective Robustness in Deep Reinforcement Learning.
CoRR
Jack Koch, Lauro Langosco, Jacob Pfau, James Le, Lee Sharkey
2021 J jnl
Robust Semantic Interpretability: Revisiting Concept Activation Vectors.
CoRR
Jacob Pfau, Albert T. Young, Jerome Wei, Maria L. Wei, Michael J. Keiser
2021 J jnl
Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models.
npj Digit. Medicine
Albert T. Young, Kristen Fernandez, Jacob Pfau, Rasika Reddy, Nhat Anh Cao, Max Y. von Franque, Arjun Johal, Benjamin V. Wu, Rachel R. Wu, Jennifer Y. Chen, Raj P. Fadadu, Juan A. Vasquez, Andrew Tam, Michael J. Keiser, Maria L. Wei
2019 J jnl
Global Saliency: Aggregating Saliency Maps to Assess Dataset Artefact Bias.
CoRR
Jacob Pfau, Albert T. Young, Maria L. Wei, Michael J. Keiser