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János Kramár
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2020 – today
- 2024
- [i19]János Kramár, Tom Lieberum, Rohin Shah, Neel Nanda:
AtP*: An efficient and scalable method for localizing LLM behaviour to components. CoRR abs/2403.00745 (2024) - [i18]Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Tom Lieberum, Vikrant Varma, János Kramár, Rohin Shah, Neel Nanda:
Improving Dictionary Learning with Gated Sparse Autoencoders. CoRR abs/2404.16014 (2024) - [i17]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:
On scalable oversight with weak LLMs judging strong LLMs. CoRR abs/2407.04622 (2024) - [i16]Senthooran Rajamanoharan, Tom Lieberum, Nicolas Sonnerat, Arthur Conmy, Vikrant Varma, János Kramár, Neel Nanda:
Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders. CoRR abs/2407.14435 (2024) - [i15]Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Nicolas Sonnerat, Vikrant Varma, János Kramár, Anca D. Dragan, Rohin Shah, Neel Nanda:
Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2. CoRR abs/2408.05147 (2024) - 2023
- [c11]David Lindner, János Kramár, Sebastian Farquhar, Matthew Rahtz, Tom McGrath, Vladimir Mikulik:
Tracr: Compiled Transformers as a Laboratory for Interpretability. NeurIPS 2023 - [i14]David Lindner, János Kramár, Matthew Rahtz, Thomas McGrath, Vladimir Mikulik:
Tracr: Compiled Transformers as a Laboratory for Interpretability. CoRR abs/2301.05062 (2023) - [i13]Victoria Krakovna, János Kramár:
Power-seeking can be probable and predictive for trained agents. CoRR abs/2304.06528 (2023) - [i12]Tom Lieberum, Matthew Rahtz, János Kramár, Neel Nanda, Geoffrey Irving, Rohin Shah, Vladimir Mikulik:
Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla. CoRR abs/2307.09458 (2023) - [i11]Thomas McGrath, Matthew Rahtz, János Kramár, Vladimir Mikulik, Shane Legg:
The Hydra Effect: Emergent Self-repair in Language Model Computations. CoRR abs/2307.15771 (2023) - [i10]Vikrant Varma, Rohin Shah, Zachary Kenton, János Kramár, Ramana Kumar:
Explaining grokking through circuit efficiency. CoRR abs/2309.02390 (2023) - 2022
- [c10]Ian Gemp, Rahul Savani, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár:
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. AAMAS 2022: 507-515 - 2021
- [c9]Yoram Bachrach, Ian Gemp, Marta Garnelo, János Kramár, Tom Eccles, Dan Rosenbaum, Thore Graepel:
A Neural Network Auction For Group Decision Making Over a Continuous Space. IJCAI 2021: 4976-4979 - [i9]Ian Gemp, Rahul Savani
, Marc Lanctot, Yoram Bachrach, Thomas W. Anthony, Richard Everett, Andrea Tacchetti, Tom Eccles, János Kramár:
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. CoRR abs/2106.01285 (2021) - 2020
- [c8]János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti:
Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions. COIN(E)@AAMAS 2020: 114-130 - [c7]Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach:
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. NeurIPS 2020 - [i8]János Kramár, Neil C. Rabinowitz, Tom Eccles, Andrea Tacchetti:
Should I tear down this wall? Optimizing social metrics by evaluating novel actions. CoRR abs/2004.07625 (2020) - [i7]Thomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett, Satinder Singh, Thore Graepel, Yoram Bachrach:
Learning to Play No-Press Diplomacy with Best Response Policy Iteration. CoRR abs/2006.04635 (2020)
2010 – 2019
- 2019
- [c6]Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo:
The Imitation Game: Learned Reciprocity in Markov games. AAMAS 2019: 1934-1936 - [c5]Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, János Kramár, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia:
Relational Forward Models for Multi-Agent Learning. ICLR (Poster) 2019 - [i6]Tom Eccles, Edward Hughes, János Kramár, Steven Wheelwright, Joel Z. Leibo:
Learning Reciprocity in Complex Sequential Social Dilemmas. CoRR abs/1903.08082 (2019) - [i5]Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds
OpenSpiel: A Framework for Reinforcement Learning in Games. CoRR abs/1908.09453 (2019) - 2018
- [c4]Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. Robotics: Science and Systems 2018 - [i4]Yuke Zhu, Ziyu Wang, Josh Merel, Andrei A. Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess:
Reinforcement and Imitation Learning for Diverse Visuomotor Skills. CoRR abs/1802.09564 (2018) - 2017
- [c3]David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal:
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. ICLR (Poster) 2017 - [i3]James Babcock, János Kramár, Roman V. Yampolskiy:
Guidelines for Artificial Intelligence Containment. CoRR abs/1707.08476 (2017) - 2016
- [c2]James Babcock, János Kramár, Roman Yampolskiy:
The AGI Containment Problem. AGI 2016: 53-63 - [i2]James Babcock, János Kramár, Roman Yampolskiy:
The AGI Containment Problem. CoRR abs/1604.00545 (2016) - [i1]David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal:
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. CoRR abs/1606.01305 (2016) - 2010
- [c1]Matthew Skala, Victoria Krakovna, János Kramár, Gerald Penn:
A Generalized-Zero-Preserving Method for Compact Encoding of Concept Lattices. ACL 2010: 1512-1521
Coauthor Index
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