Anian Ruoss

36 papers A* 14Journal 20Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A* conf
Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data.
ICML
David Heurtel-Depeiges, Anian Ruoss, Joel Veness, Tim Genewein
2025 A* conf
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations.
ICML
Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein
2025 A* conf
Mastering Board Games by External and Internal Planning with Language Models.
ICML
John Schultz, Jakub Adámek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev
2025 J jnl
Understanding Prompt Tuning and In-Context Learning via Meta-Learning.
CoRR
Tim Genewein, Li Kevin Wenliang, Jordi Grau-Moya, Anian Ruoss, Laurent Orseau, Marcus Hutter
2025 J jnl
Why is prompting hard? Understanding prompts on binary sequence predictors.
CoRR
Li Kevin Wenliang, Anian Ruoss, Jordi Grau-Moya, Marcus Hutter, Tim Genewein
2024 A* conf
Amortized Planning with Large-Scale Transformers: A Case Study on Chess.
NeurIPS
Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Kevin Li, Elliot Catt, John Reid, Cannada A. Lewis, Joel Veness, Tim Genewein
2024 J jnl
Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data.
CoRR
David Heurtel-Depeiges, Anian Ruoss, Joel Veness, Tim Genewein
2024 A* conf
Distributional Bellman Operators over Mean Embeddings.
ICML
Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland
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
Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search.
IJCAI
Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Matej Balog, Gheorghe Comanici, Tudor Berariu, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera-Paredes, Petar Velickovic, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner
2024 J jnl
Grandmaster-Level Chess Without Search.
CoRR
Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt, John Reid, Tim Genewein
2024 J jnl
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations.
CoRR
Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein
2024 A* conf
Language Modeling Is Compression.
ICLR
Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness
2024 A* conf
Learning Universal Predictors.
ICML
Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
2024 J jnl
Learning Universal Predictors.
CoRR
Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
2024 J jnl
Mastering Board Games by External and Internal Planning with Language Models.
CoRR
John Schultz, Jakub Adámek, Matej Jusup, Marc Lanctot, Michael Kaisers, Sarah Perrin, Daniel Hennes, Jeremy Shar, Cannada A. Lewis, Anian Ruoss, Tom Zahavy, Petar Velickovic, Laurel Prince, Satinder Singh, Eric Malmi, Nenad Tomasev
2023 J jnl
Distributional Bellman Operators over Mean Embeddings.
CoRR
Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland
2023 J jnl
Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search.
CoRR
Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Matej Balog, Gheorghe Comanici, Tudor Berariu, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera-Paredes, Petar Velickovic, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner
2023 J jnl
Language Modeling Is Compression.
CoRR
Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness
2023 A* conf
Memory-Based Meta-Learning on Non-Stationary Distributions.
ICML
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
2023 J jnl
Memory-Based Meta-Learning on Non-Stationary Distributions.
CoRR
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
2023 A* conf
Neural Networks and the Chomsky Hierarchy.
ICLR
Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Chris Cundy, Marcus Hutter, Shane Legg, Joel Veness, Pedro A. Ortega
2023 — conf
Randomized Positional Encodings Boost Length Generalization of Transformers.
ACL (2)
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
2023 J jnl
Randomized Positional Encodings Boost Length Generalization of Transformers.
CoRR
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
2022 J jnl
Beyond Bayes-optimality: meta-learning what you know you don't know.
CoRR
Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane X. Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro A. Ortega
2022 A* conf
Fair Normalizing Flows.
ICLR
Mislav Balunovic, Anian Ruoss, Martin T. Vechev
2022 — conf
Latent Space Smoothing for Individually Fair Representations.
ECCV (13)
Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2022 J jnl
Neural Networks and the Chomsky Hierarchy.
CoRR
Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega
2021 A* conf
Efficient Certification of Spatial Robustness.
AAAI
Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
2021 J jnl
Fair Normalizing Flows.
CoRR
Mislav Balunovic, Anian Ruoss, Martin T. Vechev
2021 J jnl
Latent Space Smoothing for Individually Fair Representations.
CoRR
Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
2021 A* conf
Robustness Certification for Point Cloud Models.
ICCV
Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev
2021 J jnl
Robustness Certification for Point Cloud Models.
CoRR
Tobias Lorenz, Anian Ruoss, Mislav Balunovic, Gagandeep Singh, Martin T. Vechev
2020 J jnl
Efficient Certification of Spatial Robustness.
CoRR
Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
2020 A* conf
Learning Certified Individually Fair Representations.
NeurIPS
Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev
2020 J jnl
Learning Certified Individually Fair Representations.
CoRR
Anian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev