David Lindner - RankMe

51 papers A* 9A 1Journal 37Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought? CoRR Max Kaufmann, David Lindner, Roland S. Zimmermann, Rohin Shah
2026	J	`jnl`	Evaluating and Understanding Scheming Propensity in LLM Agents. CoRR Mia Hopman, Jannes Elstner, Maria Avramidou, Amritanshu Prasad, David Lindner
2026	J	`jnl`	Frontier Models Can Take Actions at Low Probabilities. CoRR Alex Serrano, Wen Xing, David Lindner, Erik Jenner
2026	J	`jnl`	Quantifying the Necessity of Chain of Thought through Opaque Serial Depth. CoRR Jonah Brown-Cohen, David Lindner, Rohin Shah
2026	J	`jnl`	Stress-Testing Alignment Audits With Prompt-Level Strategic Deception. CoRR Oliver Daniels, Perusha Moodley, Benjamin M. Marlin, David Lindner
2025	J	`jnl`	An Approach to Technical AGI Safety and Security. CoRR 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
2025	J	`jnl`	Can Reasoning Models Obfuscate Reasoning? Stress-Testing Chain-of-Thought Monitorability. CoRR Artur Zolkowski, Wen Xing, David Lindner, Florian Tramèr, Erik Jenner
2025	J	`jnl`	Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety. CoRR 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
2025	J	`jnl`	Early Signs of Steganographic Capabilities in Frontier LLMs. CoRR Artur Zolkowski, Kei Nishimura-Gasparian, Robert McCarthy, Roland S. Zimmermann, David Lindner
2025	J	`jnl`	Evaluating Frontier Models for Stealth and Situational Awareness. CoRR Mary Phuong, Roland S. Zimmermann, Ziyue Wang, David Lindner, Victoria Krakovna, Sarah Cogan, Allan Dafoe, Lewis Ho, Rohin Shah
2025	J	`jnl`	Large language models can learn and generalize steganographic chain-of-thought under process supervision. CoRR 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
2025	A*	`conf`	MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking. ICML Sebastian Farquhar, Vikrant Varma, David Lindner, David Elson, Caleb Biddulph, Ian Goodfellow, Rohin Shah
2025	J	`jnl`	MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking. CoRR Sebastian Farquhar, Vikrant Varma, David Lindner, David K. Elson, Caleb Biddulph, Ian Goodfellow, Rohin Shah
2025	J	`jnl`	Practical challenges of control monitoring in frontier AI deployments. CoRR David Lindner, Charlie Griffin, Tomek Korbak, Roland S. Zimmermann, Geoffrey Irving, Sebastian Farquhar, Alan Cooney
2024	J	`jnl`	Evaluating Frontier Models for Dangerous Capabilities. CoRR 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
2024	A	`conf`	Learning Safety Constraints from Demonstrations with Unknown Rewards. AISTATS David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2024	J	`jnl`	MISR: Measuring Instrumental Self-Reasoning in Frontier Models. CoRR Kai Fronsdal, David Lindner
2024	J	`jnl`	Mapping out the Space of Human Feedback for Reinforcement Learning: A Conceptual Framework. CoRR Yannick Metz, David Lindner, Raphaël Baur, Mennatallah El-Assady
2024	A*	`conf`	On scalable oversight with weak LLMs judging strong LLMs. NeurIPS 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
2024	J	`jnl`	On scalable oversight with weak LLMs judging strong LLMs. CoRR 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
2024	J	`jnl`	Towards evaluations-based safety cases for AI scheming. CoRR 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
2024	J	`jnl`	ViSTa Dataset: Do vision-language models understand sequential tasks? CoRR Evzen Wybitul, Evan Ryan Gunter, Mikhail Seleznyov, David Lindner
2024	A*	`conf`	Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning. ICLR Juan Rocamonde, Victoriano Montesinos, Elvis Nava, Ethan Perez, David Lindner
2023	—	`—`	Algorithmic Foundations for Safe and Efficient Reinforcement Learning from Human Feedback. David Lindner
2023	J	`jnl`	GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems. Artif. Intell. Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
2023	J	`jnl`	Learning Safety Constraints from Demonstrations with Unknown Rewards. CoRR David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
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	J	`jnl`	RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback. CoRR Yannick Metz, David Lindner, Raphaël Baur, Daniel A. Keim, Mennatallah El-Assady
2023	A*	`conf`	Tracr: Compiled Transformers as a Laboratory for Interpretability. NeurIPS David Lindner, János Kramár, Sebastian Farquhar, Matthew Rahtz, Tom McGrath, Vladimir Mikulik
2023	J	`jnl`	Tracr: Compiled Transformers as a Laboratory for Interpretability. CoRR David Lindner, János Kramár, Matthew Rahtz, Thomas McGrath, Vladimir Mikulik
2023	J	`jnl`	Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning. CoRR Juan Rocamonde, Victoriano Montesinos, Elvis Nava, Ethan Perez, David Lindner
2022	A*	`conf`	Active Exploration for Inverse Reinforcement Learning. NeurIPS David Lindner, Andreas Krause, Giorgia Ramponi
2022	J	`jnl`	Active Exploration for Inverse Reinforcement Learning. CoRR David Lindner, Andreas Krause, Giorgia Ramponi
2022	J	`jnl`	Humans are not Boltzmann Distributions: Challenges and Opportunities for Modelling Human Feedback and Interaction in Reinforcement Learning. CoRR David Lindner, Mennatallah El-Assady
2022	A*	`conf`	Interactively Learning Preference Constraints in Linear Bandits. ICML David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2022	J	`jnl`	Interactively Learning Preference Constraints in Linear Bandits. CoRR David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause
2022	J	`jnl`	Red-Teaming the Stable Diffusion Safety Filter. CoRR Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, Florian Tramèr
2022	J	`jnl`	Scalable Safe Exploration for Global Optimization of Dynamical Systems. CoRR Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann
2021	A*	`conf`	Addressing the Long-term Impact of ML Decisions via Policy Regret. IJCAI David Lindner, Hoda Heidari, Andreas Krause
2021	J	`jnl`	Addressing the Long-term Impact of ML Decisions via Policy Regret. CoRR David Lindner, Hoda Heidari, Andreas Krause
2021	—	`conf`	Challenges for Using Impact Regularizers to Avoid Negative Side Effects. SafeAI@AAAI David Lindner, Kyle Matoba, Alexander Meulemans
2021	J	`jnl`	Challenges for Using Impact Regularizers to Avoid Negative Side Effects. CoRR David Lindner, Kyle Matoba, Alexander Meulemans
2021	A*	`conf`	Information Directed Reward Learning for Reinforcement Learning. NeurIPS David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
2021	J	`jnl`	Information Directed Reward Learning for Reinforcement Learning. CoRR David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause
2021	A*	`conf`	Learning What To Do by Simulating the Past. ICLR David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan
2021	J	`jnl`	Learning What To Do by Simulating the Past. CoRR David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan
2019	—	`conf`	Detecting Spiky Corruption in Markov Decision Processes. AISafety@IJCAI Jason Mancuso, Tomasz Kisielewski, David Lindner, Alok Singh
2019	J	`jnl`	Detecting Spiky Corruption in Markov Decision Processes. CoRR Jason Mancuso, Tomasz Kisielewski, David Lindner, Alok Singh
2019	—	`conf`	Sensing Social Media Signals for Cryptocurrency News. WWW (Companion Volume) Johannes Beck, Roberta Huang, David Lindner, Tian Guo, Ce Zhang, Dirk Helbing, Nino Antulov-Fantulin
2019	J	`jnl`	Sensing Social Media Signals for Cryptocurrency News. CoRR Johannes Beck, Roberta Huang, David Lindner, Tian Guo, Ce Zhang, Dirk Helbing, Nino Antulov-Fantulin