A Generalized-Zero-Preserving Method for Compact Encoding of Concept Lattices. - Matthew Skala; Victoria Krakovna; János Kramár; Gerald Penn (ACL, 2010)

The AGI Containment Problem. - James Babcock; János Kramár; Roman Yampolskiy (AGI, 2016)

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Hugo Larochelle; Aaron C. Courville; Chris Pal (CoRR, 2016)

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. - David Krueger 001; Tegan Maharaj; János Kramár; Mohammad Pezeshki; Nicolas Ballas; Nan Rosemary Ke; Anirudh Goyal; Yoshua Bengio; Aaron C. Courville; Christopher J. Pal (ICLR (Poster), 2017)

Guidelines for Artificial Intelligence Containment. - James Babcock; János Kramár; Roman V. Yampolskiy (CoRR, 2017)

Reinforcement and Imitation Learning for Diverse Visuomotor Skills. - Yuke Zhu; Ziyu Wang 001; Josh Merel; Andrei A. Rusu; Tom Erez; Serkan Cabi; Saran Tunyasuvunakool; János Kramár; Raia Hadsell; Nando de Freitas; Nicolas Heess (Robotics: Science and Systems, 2018)

The Imitation Game: Learned Reciprocity in Markov games. - Tom Eccles; Edward Hughes 001; János Kramár; Steven Wheelwright; Joel Z. Leibo (AAMAS, 2019)

Relational Forward Models for Multi-Agent Learning. - 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 (ICLR (Poster), 2019)

Learning Reciprocity in Complex Sequential Social Dilemmas. - Tom Eccles; Edward Hughes 001; János Kramár; Steven Wheelwright; Joel Z. Leibo (CoRR, 2019)

OpenSpiel: A Framework for Reinforcement Learning in Games. - Marc Lanctot; Edward Lockhart; Jean-Baptiste Lespiau; Vinícius Flores Zambaldi; Satyaki Upadhyay; Julien Pérolat; Sriram Srinivasan 005; Finbarr Timbers; Karl Tuyls; Shayegan Omidshafiei; Daniel Hennes; Dustin Morrill; et al. (CoRR, 2019)

Should I Tear down This Wall? Optimizing Social Metrics by Evaluating Novel Actions. - János Kramár; Neil C. Rabinowitz; Tom Eccles; Andrea Tacchetti (COIN(E)@AAMAS, 2020)

Learning to Play No-Press Diplomacy with Best Response Policy Iteration. - Thomas W. Anthony 001; Tom Eccles; Andrea Tacchetti; János Kramár; Ian Gemp; Thomas C. Hudson; Nicolas Porcel; Marc Lanctot; Julien Pérolat; Richard Everett 001; Satinder Singh 001; Thore Graepel; et al. (NeurIPS, 2020)

A Neural Network Auction For Group Decision Making Over a Continuous Space. - Yoram Bachrach; Ian Gemp; Marta Garnelo; János Kramár; Tom Eccles; Dan Rosenbaum; Thore Graepel (IJCAI, 2021)

Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent. - Ian Gemp; Rahul Savani; Marc Lanctot; Yoram Bachrach; Thomas W. Anthony 001; Richard Everett 001; Andrea Tacchetti; Tom Eccles; János Kramár (AAMAS, 2022)

Tracr: Compiled Transformers as a Laboratory for Interpretability. - David Lindner; János Kramár; Sebastian Farquhar; Matthew Rahtz; Tom McGrath; Vladimir Mikulik (NeurIPS, 2023)

Tracr: Compiled Transformers as a Laboratory for Interpretability. - David Lindner; János Kramár; Matthew Rahtz; Thomas McGrath; Vladimir Mikulik (CoRR, 2023)

Power-seeking can be probable and predictive for trained agents. - Victoria Krakovna; János Kramár (CoRR, 2023)

Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla. - Tom Lieberum; Matthew Rahtz; János Kramár; Neel Nanda; Geoffrey Irving; Rohin Shah; Vladimir Mikulik (CoRR, 2023)

The Hydra Effect: Emergent Self-repair in Language Model Computations. - Thomas McGrath; Matthew Rahtz; János Kramár; Vladimir Mikulik; Shane Legg (CoRR, 2023)

Explaining grokking through circuit efficiency. - Vikrant Varma; Rohin Shah; Zachary Kenton; János Kramár; Ramana Kumar (CoRR, 2023)

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 (NeurIPS, 2024)

Improving Sparse Decomposition of Language Model Activations with Gated Sparse Autoencoders. - Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Tom Lieberum; Vikrant Varma; János Kramár; Rohin Shah; Neel Nanda (NeurIPS, 2024)

AtP*: An efficient and scalable method for localizing LLM behaviour to components. - János Kramár; Tom Lieberum; Rohin Shah; Neel Nanda (CoRR, 2024)

Improving Dictionary Learning with Gated Sparse Autoencoders. - Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Tom Lieberum; Vikrant Varma; János Kramár; Rohin Shah; Neel Nanda (CoRR, 2024)

Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders. - Senthooran Rajamanoharan; Tom Lieberum; Nicolas Sonnerat; Arthur Conmy; Vikrant Varma; János Kramár; Neel Nanda (CoRR, 2024)

Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2. - Tom Lieberum; Senthooran Rajamanoharan; Arthur Conmy; Lewis Smith; Nicolas Sonnerat; Vikrant Varma; János Kramár; Anca D. Dragan; Rohin Shah; Neel Nanda (CoRR, 2024)