Rohin Shah - RankMe

55 papers A* 11A 1Journal 37Unranked 5

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`	Building Production-Ready Probes For Gemini. CoRR János Kramár, Joshua Engels, Zheng Wang, Bilal Chughtai, Rohin Shah, Neel Nanda, Arthur Conmy
2026	J	`jnl`	Quantifying the Necessity of Chain of Thought through Opaque Serial Depth. CoRR Jonah Brown-Cohen, David Lindner, Rohin Shah
2025	J	`jnl`	A Pragmatic Way to Measure Chain-of-Thought Monitorability. CoRR Scott Emmons, Roland S. Zimmermann, David K. Elson, Rohin Shah
2025	J	`jnl`	A Rosetta Stone for AI Benchmarks. CoRR Anson Ho, Jean-Stanislas Denain, David Atanasov, Samuel Albanie, Rohin Shah
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`	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`	Consistency Training Helps Stop Sycophancy and Jailbreaks. CoRR Alex Irpan, Alexander Matt Turner, Mark Kurzeja, David K. Elson, Rohin Shah
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`	Evaluating the Goal-Directedness of Large Language Models. CoRR Tom Everitt, Cristina Garbacea, Alexis Bellot, Jonathan Richens, Henry Papadatos, Siméon Campos, Rohin Shah
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`	When Chain of Thought is Necessary, Language Models Struggle to Evade Monitors. CoRR Scott Emmons, Erik Jenner, David K. Elson, Rif A. Saurous, Senthooran Rajamanoharan, Heng Chen, Irhum Shafkat, Rohin Shah
2024	J	`jnl`	AtP*: An efficient and scalable method for localizing LLM behaviour to components. CoRR János Kramár, Tom Lieberum, Rohin Shah, Neel Nanda
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	J	`jnl`	Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2. CoRR Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Nicolas Sonnerat, Vikrant Varma, János Kramár, Anca D. Dragan, Rohin Shah, Neel Nanda
2024	J	`jnl`	Improving Dictionary Learning with Gated Sparse Autoencoders. CoRR Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Tom Lieberum, Vikrant Varma, János Kramár, Rohin Shah, Neel Nanda
2024	A*	`conf`	Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders. NeurIPS Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Tom Lieberum, Vikrant Varma, János Kramár, Rohin Shah, Neel Nanda
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
2023	A*	`conf`	BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks. NeurIPS Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Rohin Shah
2023	J	`jnl`	BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks. CoRR Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Rohin Shah
2023	J	`jnl`	Challenges with unsupervised LLM knowledge discovery. CoRR Sebastian Farquhar, Vikrant Varma, Zachary Kenton, Johannes Gasteiger, Vladimir Mikulik, Rohin Shah
2023	J	`jnl`	Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla. CoRR Tom Lieberum, Matthew Rahtz, János Kramár, Neel Nanda, Geoffrey Irving, Rohin Shah, Vladimir Mikulik
2023	J	`jnl`	Explaining grokking through circuit efficiency. CoRR Vikrant Varma, Rohin Shah, Zachary Kenton, János Kramár, Ramana Kumar
2023	A*	`conf`	SIRL: Similarity-based Implicit Representation Learning. HRI Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan
2023	J	`jnl`	SIRL: Similarity-based Implicit Representation Learning. CoRR Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan
2023	J	`jnl`	Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. CoRR Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah
2022	J	`jnl`	An Empirical Investigation of Representation Learning for Imitation. CoRR Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
2022	J	`jnl`	Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals. CoRR Rohin Shah, Vikrant Varma, Ramana Kumar, Mary Phuong, Victoria Krakovna, Jonathan Uesato, Zac Kenton
2022	J	`jnl`	Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. CoRR Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum
2021	—	`conf`	An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
2021	J	`jnl`	Choice Set Misspecification in Reward Inference. CoRR Rachel Freedman, Rohin Shah, Anca D. Dragan
2021	J	`jnl`	Combining Reward Information from Multiple Sources. CoRR Dmitrii Krasheninnikov, Rohin Shah, Herke van Hoof
2021	A	`conf`	Evaluating the Robustness of Collaborative Agents. AAMAS Paul A. Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
2021	J	`jnl`	Evaluating the Robustness of Collaborative Agents. CoRR Paul A. Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah
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
2021	A*	`conf`	Optimal Policies Tend To Seek Power. NeurIPS Alexander Matt Turner, Logan Smith, Rohin Shah, Andrew Critch, Prasad Tadepalli
2021	—	`conf`	Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. NeurIPS (Competition and Demos) Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum
2021	J	`jnl`	The MineRL BASALT Competition on Learning from Human Feedback. CoRR Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D. Dragan
2021	—	`conf`	Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. NeurIPS (Competition and Demos) Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Lucas Cazzonelli, Cedric Kulbach, Nicholas Popovic, Marvin Schweizer, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah
2020	—	`conf`	Choice Set Misspecification in Reward Inference. AISafety@IJCAI Rachel Freedman, Rohin Shah, Anca D. Dragan
2020	—	`—`	Extracting and Using Preference Information from the State of the World. Rohin Shah
2020	A*	`conf`	The MAGICAL Benchmark for Robust Imitation. NeurIPS Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell
2020	J	`jnl`	The MAGICAL Benchmark for Robust Imitation. CoRR Sam Toyer, Rohin Shah, Andrew Critch, Stuart Russell
2019	A*	`conf`	On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference. ICML Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca D. Dragan
2019	J	`jnl`	On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference. CoRR Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca D. Dragan
2019	A*	`conf`	On the Utility of Learning about Humans for Human-AI Coordination. NeurIPS Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan
2019	J	`jnl`	On the Utility of Learning about Humans for Human-AI Coordination. CoRR Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan
2019	—	`conf`	Preferences Implicit in the State of the World. ICLR (Poster) Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan
2019	J	`jnl`	Preferences Implicit in the State of the World. CoRR Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan
2018	J	`jnl`	Active Inverse Reward Design. CoRR Sören Mindermann, Rohin Shah, Adam Gleave, Dylan Hadfield-Menell
2016	J	`jnl`	SIMPL: A DSL for Automatic Specialization of Inference Algorithms. CoRR Rohin Shah, Emina Torlak, Rastislav Bodík
2014	A*	`conf`	Chlorophyll: synthesis-aided compiler for low-power spatial architectures. PLDI Phitchaya Mangpo Phothilimthana, Tikhon Jelvis, Rohin Shah, Nishant Totla, Sarah E. Chasins, Rastislav Bodík