Subsymbolic User Modeling in Adaptive Hypermedia. - Katja Hofmann (AIED, 2005)

Modeling Engagement in Educational Adaptive Hypermedia. - Jabari O. Pulliam; Robert Sajan; Katja Hofmann (AIED, 2007)

The University of Amsterdam's Question Answering System at QA@CLEF 2007. - Valentin Jijkoun; Katja Hofmann; David Ahn; Mahboob Alam Khalid; Joris van Rantwijk; Maarten de Rijke; Erik F. Tjong Kim Sang (CLEF, 2007)

The University of Amsterdam at CLEF@QA 2007. - Valentin Jijkoun; Katja Hofmann; David Ahn; Mahboob Alam Khalid; Joris van Rantwijk; Maarten de Rijke; Erik F. Tjong Kim Sang (CLEF (Working Notes), 2007)

Automatic extension of non-english wordnets. - Katja Hofmann; Erik F. Tjong Kim Sang (SIGIR, 2007)

Query and Document Models for Enterprise Search. - Krisztian Balog; Katja Hofmann; Wouter Weerkamp; Maarten de Rijke (TREC, 2007)

The University of Amsterdam at the TREC 2007 QA Track. - Katja Hofmann; Valentin Jijkoun; Mahboob Alam Khalid; Joris van Rantwijk; Erik F. Tjong Kim Sang (TREC, 2007)

Unobtrusive User Modeling for Adaptive Hypermedia. - Hilary J. Holz; Katja Hofmann; Catherine Reed (Int. J. Pattern Recognit. Artif. Intell., 2007)

An Exploratory Study of User Goals and Strategies in Podcast Search. - Jana Besser; Katja Hofmann; Martha A. Larson (LWA, 2008)

Assessing concept selection for video retrieval. - Bouke Huurnink; Katja Hofmann; Maarten de Rijke (Multimedia Information Retrieval, 2008)

Unobtrusive User Modeling For Adaptive Hypermedia. - Hilary J. Holz; Katja Hofmann; Catherine Reed (Personalization Techniques and Recommender Systems, 2008)

The impact of document structure on keyphrase extraction. - Katja Hofmann; Manos Tsagkias; Edgar Meij; Maarten de Rijke (CIKM, 2009)

A Semantic Perspective on Query Log Analysis. - Katja Hofmann; Maarten de Rijke; Bouke Huurnink; Edgar Meij (CLEF (Working Notes), 2009)

Lexical Patterns or Dependency Patterns: Which Is Better for Hypernym Extraction? - Erik F. Tjong Kim Sang; Katja Hofmann (CoNLL, 2009)

Generating a Non-English Subjectivity Lexicon: Relations That Matter. - Valentin Jijkoun; Katja Hofmann (EACL, 2009)

Heuristic Ranking and Diversification of Web Documents. - Jiyin He; Krisztian Balog; Katja Hofmann; Edgar Meij; Maarten de Rijke; Manos Tsagkias; Wouter Weerkamp (TREC, 2009)

Validating Query Simulators: An Experiment Using Commercial Searches and Purchases. - Bouke Huurnink; Katja Hofmann; Maarten de Rijke; Marc Bron (CLEF, 2010)

Comparing click-through data to purchase decisions for retrieval evaluation. - Katja Hofmann; Bouke Huurnink; Marc Bron; Maarten de Rijke (SIGIR, 2010)

The University of Amsterdam at TREC 2010: Session, Entity and Relevance Feedback. - Marc Bron; Jiyin He; Katja Hofmann; Edgar Meij; Maarten de Rijke; Manos Tsagkias; Wouter Weerkamp (TREC, 2010)

Contextual factors for finding similar experts. - Katja Hofmann; Krisztian Balog; Toine Bogers; Maarten de Rijke (J. Assoc. Inf. Sci. Technol., 2010)

Podcast search: user goals and retrieval technologies. - Jana Besser; Martha A. Larson; Katja Hofmann (Online Inf. Rev., 2010)

A probabilistic method for inferring preferences from clicks. - Katja Hofmann; Shimon Whiteson; Maarten de Rijke (CIKM, 2011)

Balancing Exploration and Exploitation in Learning to Rank Online. - Katja Hofmann; Shimon Whiteson; Maarten de Rijke (ECIR, 2011)

Adapting Rankers Online. - Katja Hofmann; Shimon Whiteson; Maarten de Rijke (IRFC, 2011)

Search engines that learn online. - Katja Hofmann (SIGIR, 2011)

The University of Amsterdam at the TREC 2011 Session Track. - Bouke Huurnink; Richard Berendsen; Katja Hofmann; Edgar Meij; Maarten de Rijke (TREC, 2011)

DIR 2011: the eleventh Dutch-Belgian information retrieval workshop. - Corrado Boscarino; Katja Hofmann; Valentin Jijkoun; Edgar Meij; Maarten de Rijke; Wouter Weerkamp (SIGIR Forum, 2011)

Extraction of Hypernymy Information from Text∗. - Erik Tjong Kim Sang; Katja Hofmann; Maarten de Rijke (Interactive Multi-modal Question-Answering, 2011)

On caption bias in interleaving experiments. - Katja Hofmann; Fritz Behr; Filip Radlinski (CIKM, 2012)

Estimating interleaved comparison outcomes from historical click data. - Katja Hofmann; Shimon Whiteson; Maarten de Rijke (CIKM, 2012)

Learning to Rank from Relevance Feedback for e-Discovery. - Peter Lubell-Doughtie; Katja Hofmann (ECIR, 2012)

Evaluating aggregated search using interleaving. - Aleksandr Chuklin; Anne Schuth; Katja Hofmann; Pavel Serdyukov; Maarten de Rijke (CIKM, 2013)

Lerot: an online learning to rank framework. - Anne Schuth; Katja Hofmann; Shimon Whiteson; Maarten de Rijke (LivingLab@CIKM, 2013)

Reusing Historical Interaction Data for Faster Online Learning to Rank for IR. - Katja Hofmann; Anne Schuth; Shimon Whiteson; Maarten de Rijke (DIR, 2013)

Practical Online Retrieval Evaluation. - Filip Radlinski; Katja Hofmann (ECIR, 2013)

Balancing exploration and exploitation in listwise and pairwise online learning to rank for information retrieval. - Katja Hofmann; Shimon Whiteson; Maarten de Rijke (Inf. Retr., 2013)

Fast and reliable online learning to rank for information retrieval. - Katja Hofmann (SIGIR Forum, 2013)

Fidelity, Soundness, and Efficiency of Interleaved Comparison Methods. - Katja Hofmann; Shimon Whiteson; Maarten de Rijke (ACM Trans. Inf. Syst., 2013)

Cornetto: A Combinatorial Lexical Semantic Database for Dutch. - Piek Vossen; Isa Maks; Roxane Segers; Hennie van der Vliet; Marie-Francine Moens; Katja Hofmann; Erik Tjong Kim Sang; Maarten de Rijke (Essential Speech and Language Technology for Dutch, 2013)

An Eye-tracking Study of User Interactions with Query Auto Completion. - Katja Hofmann; Bhaskar Mitra 001; Filip Radlinski; Milad Shokouhi (CIKM, 2014)

Effects of Position Bias on Click-Based Recommender Evaluation. - Katja Hofmann; Anne Schuth; Alejandro Bellogín; Maarten de Rijke (ECIR, 2014)

Online Experimentation for Information Retrieval. - Katja Hofmann (RuSSIR, 2014)

On user interactions with query auto-completion. - Bhaskar Mitra 001; Milad Shokouhi; Filip Radlinski; Katja Hofmann (SIGIR, 2014)

"Learning to rank for information retrieval from user interactions" by K. Hofmann, S. Whiteson, A. Schuth, and M. de Rijke with Martin Vesely as coordinator. - Katja Hofmann; Shimon Whiteson; Anne Schuth; Maarten de Rijke (SIGWEB Newsl., 2014)

Contextual Dueling Bandits. - Miroslav Dudík; Katja Hofmann; Robert E. Schapire; Aleksandrs Slivkins; Masrour Zoghi (COLT, 2015)

Predicting Search Satisfaction Metrics with Interleaved Comparisons. - Anne Schuth; Katja Hofmann; Filip Radlinski (SIGIR, 2015)

Online Learning to Rank: Absolute vs. Relative. - Yiwei Chen; Katja Hofmann (WWW (Companion Volume), 2015)

Collective Noise Contrastive Estimation for Policy Transfer Learning. - Weinan Zhang 001; Ulrich Paquet; Katja Hofmann (AAAI, 2016)

The Malmo Platform for Artificial Intelligence Experimentation. - Matthew Johnson 003; Katja Hofmann; Tim Hutton; David Bignell (IJCAI, 2016)

Towards Conversational Recommender Systems. - Konstantina Christakopoulou; Filip Radlinski; Katja Hofmann (KDD, 2016)

Memory Lens: How Much Memory Does an Agent Use? - Christoph Dann; Katja Hofmann; Sebastian Nowozin (CoRR, 2016)

Experimental and causal view on information integration in autonomous agents. - Philipp Geiger; Katja Hofmann; Bernhard Schölkopf (CoRR, 2016)

A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games. - Felix Leibfried; Nate Kushman; Katja Hofmann (CoRR, 2016)

Online Evaluation for Information Retrieval. - Katja Hofmann; Lihong Li 001; Filip Radlinski (Found. Trends Inf. Retr., 2016)

Asynchronous Data Aggregation for Training End to End Visual Control Networks. - Mathew Monfort; Matthew Johnson 003; Aude Oliva; Katja Hofmann (AAMAS, 2017)

Spontaneous Interactions with a Virtually Embodied Intelligent Assistant in Minecraft. - Fraser Allison; Ewa Luger; Katja Hofmann (CHI Extended Abstracts, 2017)

A New AI Evaluation Cosmos: Ready to Play the Game? - José Hernández-Orallo; Marco Baroni; Jordi Bieger; Nader Chmait; David L. Dowe; Katja Hofmann; Fernando Martínez-Plumed; Claes Strannegård; Kristinn R. Thórisson (AI Mag., 2017)

The Atari Grand Challenge Dataset. - Vitaly Kurin; Sebastian Nowozin; Katja Hofmann; Lucas Beyer; Bastian Leibe (CoRR, 2017)

Advancements in Dueling Bandits. - Yanan Sui; Masrour Zoghi; Katja Hofmann; Yisong Yue (IJCAI, 2018)

Cross Domain Regularization for Neural Ranking Models using Adversarial Learning. - Daniel Cohen; Bhaskar Mitra 001; Katja Hofmann; W. Bruce Croft (SIGIR, 2018)

Meta Reinforcement Learning with Latent Variable Gaussian Processes. - Steindór Sæmundsson; Katja Hofmann; Marc Peter Deisenroth (UAI, 2018)

Variational Inference for Data-Efficient Model Learning in POMDPs. - Sebastian Tschiatschek; Kai Arulkumaran; Jan Stühmer; Katja Hofmann (CoRR, 2018)

Depth and nonlinearity induce implicit exploration for RL. - Justas Dauparas; Ryota Tomioka; Katja Hofmann (CoRR, 2018)

CAML: Fast Context Adaptation via Meta-Learning. - Luisa M. Zintgraf; Kyriacos Shiarlis; Vitaly Kurin; Katja Hofmann; Shimon Whiteson (CoRR, 2018)

Successor Uncertainties: exploration and uncertainty in temporal difference learning. - David Janz; Jiri Hron; José Miguel Hernández-Lobato; Katja Hofmann; Sebastian Tschiatschek (CoRR, 2018)

How Players Speak to an Intelligent Game Character Using Natural Language Messages. - Fraser Allison; Ewa Luger; Katja Hofmann (Trans. Digit. Games Res. Assoc., 2018)

Minecraft as AI Playground and Laboratory. - Katja Hofmann (CHI PLAY, 2019)

MazeExplorer: A Customisable 3D Benchmark for Assessing Generalisation in Reinforcement Learning. - Luke Harries; Sebastian Lee; Jaroslaw Rzepecki; Katja Hofmann; Sam Devlin (CoG, 2019)

Win or Learn Fast Proximal Policy Optimisation. - Dino Stephen Ratcliffe; Katja Hofmann; Sam Devlin (CoG, 2019)

Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments. - Rémy Portelas; Cédric Colas; Katja Hofmann; Pierre-Yves Oudeyer (CoRL, 2019)

Fast Context Adaptation via Meta-Learning. - Luisa M. Zintgraf; Kyriacos Shiarlis; Vitaly Kurin; Katja Hofmann; Shimon Whiteson (ICML, 2019)

Better Exploration with Optimistic Actor Critic. - Kamil Ciosek; Quan Vuong; Robert Tyler Loftin; Katja Hofmann (NeurIPS, 2019)

Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. - Maximilian Igl; Kamil Ciosek; Yingzhen Li; Sebastian Tschiatschek; Cheng Zhang 005; Sam Devlin; Katja Hofmann (NeurIPS, 2019)

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning. - David Janz; Jiri Hron; Przemyslaw Mazur; Katja Hofmann; José Miguel Hernández-Lobato; Sebastian Tschiatschek (NeurIPS, 2019)

The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition. - Diego Pérez-Liébana; Katja Hofmann; Sharada Prasanna Mohanty; Noburu Kuno; André Kramer; Sam Devlin; Raluca D. Gaina; Daniel Ionita (CoRR, 2019)

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors. - William H. Guss; Cayden R. Codel; Katja Hofmann; Brandon Houghton; Noburu Kuno; Stephanie Milani; Sharada P. Mohanty; Diego Perez Liebana; Ruslan Salakhutdinov; Nicholay Topin; Manuela Veloso; Phillip Wang (CoRR, 2019)

Near-Optimal Online Egalitarian learning in General Sum Repeated Matrix Games. - Aristide C. Y. Tossou; Christos Dimitrakakis; Jaroslaw Rzepecki; Katja Hofmann (CoRR, 2019)

Variational Integrator Networks for Physically Meaningful Embeddings. - Steindór Sæmundsson; Alexander Terenin; Katja Hofmann; Marc Peter Deisenroth (CoRR, 2019)

"It's Unwieldy and It Takes a Lot of Time" - Challenges and Opportunities for Creating Agents in Commercial Games. - Mikhail Jacob; Sam Devlin; Katja Hofmann (AIIDE, 2020)

Variational Integrator Networks for Physically Structured Embeddings. - Steindór Sæmundsson; Alexander Terenin; Katja Hofmann; Marc Peter Deisenroth (AISTATS, 2020)

Combining No-regret and Q-learning. - Ian A. Kash; Michael Sullins; Katja Hofmann (AAMAS, 2020)

A Novel Individually Rational Objective In Multi-Agent Multi-Armed Bandits: Algorithms and Regret Bounds. - Aristide C. Y. Tossou; Christos Dimitrakakis; Jaroslaw Rzepecki; Katja Hofmann (AAMAS, 2020)

AMRL: Aggregated Memory For Reinforcement Learning. - Jacob Beck; Kamil Ciosek; Sam Devlin; Sebastian Tschiatschek; Cheng Zhang 005; Katja Hofmann (ICLR, 2020)

Conservative Uncertainty Estimation By Fitting Prior Networks. - Kamil Ciosek; Vincent Fortuin; Ryota Tomioka; Katja Hofmann; Richard E. Turner (ICLR, 2020)

VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. - Luisa M. Zintgraf; Kyriacos Shiarlis; Maximilian Igl; Sebastian Schulze; Yarin Gal; Katja Hofmann; Shimon Whiteson (ICLR, 2020)

Automatic Curriculum Learning For Deep RL: A Short Survey. - Rémy Portelas; Cédric Colas; Lilian Weng; Katja Hofmann; Pierre-Yves Oudeyer (IJCAI, 2020)

NeurIPS 2020 Competition and Demonstration Track: Revised selected papers. - Hugo Jair Escalante; Katja Hofmann (NeurIPS (Competition and Demos), 2020)

Trying AGAIN instead of Trying Longer: Prior Learning for Automatic Curriculum Learning. - Rémy Portelas; Katja Hofmann; Pierre-Yves Oudeyer (CoRR, 2020)

Recognizing Spatial Configurations of Objects with Graph Neural Networks. - Laetitia Teodorescu; Katja Hofmann; Pierre-Yves Oudeyer (CoRR, 2020)

Guaranteeing Reproducibility in Deep Learning Competitions. - Brandon Houghton; Stephanie Milani; Nicholay Topin; William H. Guss; Katja Hofmann; Diego Perez Liebana; Manuela Veloso; Ruslan Salakhutdinov (CoRR, 2020)

Analytic Manifold Learning: Unifying and Evaluating Representations for Continuous Control. - Rika Antonova; Maksim Maydanskiy; Danica Kragic; Sam Devlin; Katja Hofmann (CoRR, 2020)

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. - Luisa M. Zintgraf; Leo Feng; Maximilian Igl; Kristian Hartikainen; Katja Hofmann; Shimon Whiteson (CoRR, 2020)

Meta Automatic Curriculum Learning. - Rémy Portelas; Clément Romac; Katja Hofmann; Pierre-Yves Oudeyer (CoRR, 2020)

Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. - Lida Theodorou; Daniela Massiceti; Luisa M. Zintgraf; Simone Stumpf; Cecily Morrison; Edward Cutrell; Matthew Tobias Harris; Katja Hofmann (ASSETS, 2021)

Evaluating the Robustness of Collaborative Agents. - Paul A. Knott; Micah Carroll; Sam Devlin; Kamil Ciosek; Katja Hofmann; Anca D. Dragan; Rohin Shah (AAMAS, 2021)

Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. - Luisa M. Zintgraf; Sam Devlin; Kamil Ciosek; Shimon Whiteson; Katja Hofmann (AAMAS, 2021)

ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. - Daniela Massiceti; Luisa M. Zintgraf; John Bronskill; Lida Theodorou; Matthew Tobias Harris; Edward Cutrell; Cecily Morrison; Katja Hofmann; Simone Stumpf (ICCV, 2021)

Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation. - Sam Devlin; Raluca Georgescu; Ida Momennejad; Jaroslaw Rzepecki; Evelyn Zuniga; Gavin Costello; Guy Leroy; Ali Shaw; Katja Hofmann (ICML, 2021)

TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL. - Clément Romac; Rémy Portelas; Katja Hofmann; Pierre-Yves Oudeyer (ICML, 2021)

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. - Luisa M. Zintgraf; Leo Feng; Cong Lu; Maximilian Igl; Kristian Hartikainen; Katja Hofmann; Shimon Whiteson (ICML, 2021)

Memory Efficient Meta-Learning with Large Images. - John Bronskill; Daniela Massiceti; Massimiliano Patacchiola; Katja Hofmann; Sebastian Nowozin; Richard E. Turner (NeurIPS, 2021)

Grounding Spatio-Temporal Language with Transformers. - Tristan Karch; Laetitia Teodorescu; Katja Hofmann; Clément Moulin-Frier; Pierre-Yves Oudeyer (NeurIPS, 2021)

Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021. - Julia Kiseleva; Ziming Li 001; Mohammad Aliannejadi; Shrestha Mohanty; Maartje ter Hoeve; Mikhail Burtsev 001; Alexey Skrynnik; Artem Zholus; Aleksandr Panov; Kavya Srinet; Arthur Szlam; Yuxuan Sun 004; et al. (NeurIPS (Competition and Demos), 2021)

Strategically efficient exploration in competitive multi-agent reinforcement learning. - Robert Tyler Loftin; Aadirupa Saha; Sam Devlin; Katja Hofmann (UAI, 2021)

SocialAI 0.1: Towards a Benchmark to Stimulate Research on Socio-Cognitive Abilities in Deep Reinforcement Learning Agents. - Grgur Kovac; Rémy Portelas; Katja Hofmann; Pierre-Yves Oudeyer (CoRR, 2021)

Learning to Win, Lose and Cooperate through Reward Signal Evolution. - Rafal Muszynski; Katja Hofmann; Jun Wang (CoRR, 2021)

SoftDICE for Imitation Learning: Rethinking Off-policy Distribution Matching. - Mingfei Sun 001; Anuj Mahajan; Katja Hofmann; Shimon Whiteson (CoRR, 2021)

SocialAI: Benchmarking Socio-Cognitive Abilities in Deep Reinforcement Learning Agents. - Grgur Kovac; Rémy Portelas; Katja Hofmann; Pierre-Yves Oudeyer (CoRR, 2021)

NeurIPS 2021 Competition IGLU: Interactive Grounded Language Understanding in a Collaborative Environment. - Julia Kiseleva; Ziming Li 001; Mohammad Aliannejadi; Shrestha Mohanty; Maartje ter Hoeve; Mikhail Burtsev 001; Alexey Skrynnik; Artem Zholus; Aleksandr I. Panov; Kavya Srinet; Arthur Szlam; Yuxuan Sun 004; et al. (CoRR, 2021)

SpatialSim: Recognizing Spatial Configurations of Objects With Graph Neural Networks. - Laetitia Teodorescu; Katja Hofmann; Pierre-Yves Oudeyer (Frontiers Artif. Intell., 2021)

VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning. - Luisa M. Zintgraf; Sebastian Schulze; Cong Lu; Leo Feng; Maximilian Igl; Kyriacos Shiarlis; Yarin Gal; Katja Hofmann; Shimon Whiteson (J. Mach. Learn. Res., 2021)

Deterministic and Discriminative Imitation (D2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency. - Mingfei Sun 001; Sam Devlin; Katja Hofmann; Shimon Whiteson (AAAI, 2022)

How Humans Perceive Human-like Behavior in Video Game Navigation. - Evelyn Zuniga; Stephanie Milani; Guy Leroy; Jaroslaw Rzepecki; Raluca Georgescu; Ida Momennejad; David Bignell; Mingfei Sun 001; Alison Shaw; Gavin Costello; Mikhail Jacob; Sam Devlin; et al. (CHI Extended Abstracts, 2022)

Interactively Learning Preference Constraints in Linear Bandits. - David Lindner; Sebastian Tschiatschek; Katja Hofmann; Andreas Krause 001 (ICML, 2022)

Uni[MASK]: Unified Inference in Sequential Decision Problems. - Micah Carroll; Orr Paradise; Jessy Lin; Raluca Georgescu; Mingfei Sun 001; David Bignell; Stephanie Milani; Katja Hofmann; Matthew J. Hausknecht; Anca D. Dragan; Sam Devlin (NeurIPS, 2022)

Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. - Massimiliano Patacchiola; John Bronskill; Aliaksandra Shysheya; Katja Hofmann; Sebastian Nowozin; Richard E. Turner (NeurIPS, 2022)

You May Not Need Ratio Clipping in PPO. - Mingfei Sun 001; Vitaly Kurin; Guoqing Liu; Sam Devlin; Tao Qin 001; Katja Hofmann; Shimon Whiteson (CoRR, 2022)

Monotonic Improvement Guarantees under Non-stationarity for Decentralized PPO. - Mingfei Sun 001; Sam Devlin; Katja Hofmann; Shimon Whiteson (CoRR, 2022)

Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. - Micah Carroll; Jessy Lin; Orr Paradise; Raluca Georgescu; Mingfei Sun 001; David Bignell; Stephanie Milani; Katja Hofmann; Matthew J. Hausknecht; Anca D. Dragan; Sam Devlin (CoRR, 2022)

UniMASK: Unified Inference in Sequential Decision Problems. - Micah Carroll; Orr Paradise; Jessy Lin; Raluca Georgescu; Mingfei Sun 001; David Bignell; Stephanie Milani; Katja Hofmann; Matthew J. Hausknecht; Anca D. Dragan; Sam Devlin (CoRR, 2022)

Trust Region Bounds for Decentralized PPO Under Non-stationarity. - Mingfei Sun 001; Sam Devlin; Jacob Beck; Katja Hofmann; Shimon Whiteson (AAMAS, 2023)

Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. - Stephanie Milani; Arthur Juliani; Ida Momennejad; Raluca Georgescu; Jaroslaw Rzepecki; Alison Shaw; Gavin Costello; Fei Fang 001; Sam Devlin; Katja Hofmann (CHI, 2023)

Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation. - Massimiliano Patacchiola; Mingfei Sun 001; Katja Hofmann; Richard E. Turner (CoLLAs, 2023)

Imitating Human Behaviour with Diffusion Models. - Tim Pearce; Tabish Rashid; Anssi Kanervisto; David Bignell; Mingfei Sun 001; Raluca Georgescu; Sergio Valcarcel Macua; Shan Zheng Tan; Ida Momennejad; Katja Hofmann; Sam Devlin (ICLR, 2023)

Trust-Region-Free Policy Optimization for Stochastic Policies. - Mingfei Sun 001; Benjamin Ellis; Anuj Mahajan; Sam Devlin; Katja Hofmann; Shimon Whiteson (CoRR, 2023)

Learning Safety Constraints from Demonstrations with Unknown Rewards. - David Lindner; Xin Chen; Sebastian Tschiatschek; Katja Hofmann; Andreas Krause 001 (AISTATS, 2024)

Transformer Neural Autoregressive Flows. - Massimiliano Patacchiola; Aliaksandra Shysheya; Katja Hofmann; Richard E. Turner (CoRR, 2024)

Toward Human-AI Alignment in Large-Scale Multi-Player Games. - Sugandha Sharma; Guy Davidson; Khimya Khetarpal; Anssi Kanervisto; Udit Arora; Katja Hofmann; Ida Momennejad (CoRR, 2024)

Scaling Laws for Pre-training Agents and World Models. - Tim Pearce; Tabish Rashid; David Bignell; Raluca Georgescu; Sam Devlin; Katja Hofmann (CoRR, 2024)

World and Human Action Models towards gameplay ideation. - Anssi Kanervisto; David Bignell; Linda Yilin Wen; Martin Grayson; Raluca Georgescu; Sergio Valcarcel Macua; Shan Zheng Tan; Tabish Rashid; Tim Pearce; Yuhan Cao 001; Abdelhak Lemkhenter; Chentian Jiang; et al. (Nat., 2025)

Fast Autoregressive Video Generation with Diagonal Decoding. - Yang Ye; Junliang Guo; Haoyu Wu; Tianyu He; Tim Pearce; Tabish Rashid; Katja Hofmann; Jiang Bian 002 (CoRR, 2025)

Adapting Vision-Language Models for Evaluating World Models. - Mariya Hendriksen; Tabish Rashid; David Bignell; Raluca Georgescu; Abdelhak Lemkhenter; Katja Hofmann; Sam Devlin; Sarah Parisot (CoRR, 2025)