David Lindner

According to our database, David Lindner authored at least 31 papers between 2019 and 2025.

Collaborative distances:

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

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, Alan Cooney, Allan Dafoe, Anca D. Dragan, Scott Emmons, Owain Evans, David Farhi, Ryan Greenblatt, Dan Hendrycks, Marius Hobbhahn, Evan Hubinger, Geoffrey Irving, Erik Jenner, Daniel Kokotajlo, Victoria Krakovna, Shane Legg, David Lindner, David Luan, Aleksander Madry, Julian Michael, Neel Nanda, Dave Orr, Jakub Pachocki, Ethan Perez, Mary Phuong, Fabien Roger, Joshua Saxe, Buck Shlegeris, Martín Soto, Eric Steinberger, Jasmine Wang, Wojciech Zaremba, Bowen Baker, Rohin Shah, Vladimir Mikulik

CoRR, July, 2025

Early Signs of Steganographic Capabilities in Frontier LLMs.

Artur Zolkowski, Kei Nishimura-Gasparian, Robert McCarthy, Roland S. Zimmermann, David Lindner

CoRR, July, 2025

Large language models can learn and generalize steganographic chain-of-thought under process supervision.

Joey Skaf, Luis Ibañez-Lissen, Robert McCarthy, Connor Watts, Vasil Georgiv, Hannes Whittingham, Lorena González-Manzano, David Lindner, Cameron Tice, Edward James Young, Puria Radmard

CoRR, June, 2025

Evaluating Frontier Models for Stealth and Situational Awareness.

Mary Phuong, Roland S. Zimmermann, Ziyue Wang, David Lindner, Victoria Krakovna, Sarah Cogan, Allan Dafoe, Lewis Ho, Rohin Shah

CoRR, May, 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, Samuel Albanie, Scott Emmons, Sebastian Farquhar, Sébastien Krier, Senthooran Rajamanoharan, Sophie Bridgers, Tobi Ijitoye, Tom Everitt, Victoria Krakovna, Vikrant Varma, Vladimir Mikulik, Zachary Kenton, Dave Orr, Shane Legg, Noah D. Goodman, Allan Dafoe, Four Flynn, Anca D. Dragan

CoRR, April, 2025

MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking.

Sebastian Farquhar, Vikrant Varma, David Lindner, David K. Elson, Caleb Biddulph, Ian Goodfellow, Rohin Shah

CoRR, January, 2025

2024

MISR: Measuring Instrumental Self-Reasoning in Frontier Models.

Kai Fronsdal, David Lindner

CoRR, 2024

ViSTa Dataset: Do vision-language models understand sequential tasks?

Evzen Wybitul, Evan Ryan Gunter, Mikhail Seleznyov, David Lindner

CoRR, 2024

Mapping out the Space of Human Feedback for Reinforcement Learning: A Conceptual Framework.

Yannick Metz, David Lindner, Raphaël Baur, Mennatallah El-Assady

CoRR, 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

Evaluating Frontier Models for Dangerous Capabilities.

Mary Phuong, Matthew Aitchison, Elliot Catt, Sarah Cogan, Alexandre Kaskasoli, Victoria Krakovna, David Lindner, Matthew Rahtz, Yannis Assael, Sarah Hodkinson, Heidi Howard, Tom Lieberum, Ramana Kumar, Maria Abi Raad, Albert Webson, Lewis Ho, Sharon Lin, Sebastian Farquhar, Marcus Hutter, Grégoire Delétang, Anian Ruoss, Seliem El-Sayed, Sasha Brown, Anca D. Dragan, Rohin Shah, Allan Dafoe, Toby Shevlane

CoRR, 2024

On scalable oversight with weak LLMs judging strong LLMs.

Zachary Kenton, Noah Y. Siegel, János Kramár, Jonah Brown-Cohen, Samuel Albanie, Jannis Bulian, Rishabh Agarwal, David Lindner, Yunhao Tang, Noah D. Goodman, Rohin Shah

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

Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning.

Juan Rocamonde, Victoriano Montesinos, Elvis Nava, Ethan Perez, David Lindner

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning Safety Constraints from Demonstrations with Unknown Rewards.

David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems.

Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann

Artif. Intell., July, 2023

Algorithmic Foundations for Safe and Efficient Reinforcement Learning from Human Feedback.

David Lindner

PhD thesis, 2023

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

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

Trans. Mach. Learn. Res., 2023

RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback.

Yannick Metz, David Lindner, Raphaël Baur, Daniel A. Keim, Mennatallah El-Assady

CoRR, 2023

Tracr: Compiled Transformers as a Laboratory for Interpretability.

David Lindner, János Kramár, Matthew Rahtz, Thomas McGrath, Vladimir Mikulik

CoRR, 2023

Tracr: Compiled Transformers as a Laboratory for Interpretability.

David Lindner, János Kramár, Sebastian Farquhar, Matthew Rahtz, Tom McGrath, Vladimir Mikulik

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

2022

Red-Teaming the Stable Diffusion Safety Filter.

Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, Florian Tramèr

CoRR, 2022

Humans are not Boltzmann Distributions: Challenges and Opportunities for Modelling Human Feedback and Interaction in Reinforcement Learning.

David Lindner, Mennatallah El-Assady

CoRR, 2022

Scalable Safe Exploration for Global Optimization of Dynamical Systems.

Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann

CoRR, 2022

Active Exploration for Inverse Reinforcement Learning.

David Lindner, Andreas Krause, Giorgia Ramponi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Interactively Learning Preference Constraints in Linear Bandits.

David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

Proceedings of the International Conference on Machine Learning, 2022

2021

Information Directed Reward Learning for Reinforcement Learning.

David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Addressing the Long-term Impact of ML Decisions via Policy Regret.

David Lindner, Hoda Heidari, Andreas Krause

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning What To Do by Simulating the Past.

David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan

Proceedings of the 9th International Conference on Learning Representations, 2021

Challenges for Using Impact Regularizers to Avoid Negative Side Effects.

David Lindner, Kyle Matoba, Alexander Meulemans

Proceedings of the Workshop on Artificial Intelligence Safety 2021 (SafeAI 2021) co-located with the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), 2021

2019

Sensing Social Media Signals for Cryptocurrency News.

Johannes Beck, Roberta Huang, David Lindner, Tian Guo, Ce Zhang, Dirk Helbing, Nino Antulov-Fantulin

Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

Detecting Spiky Corruption in Markov Decision Processes.

Jason Mancuso, Tomasz Kisielewski, David Lindner, Alok Singh

Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the 28th International Joint Conference on Artificial Intelligence, 2019