Foerster, Jakob Nicolaus

72 publications

NeurIPS 2025 A Clean Slate for Offline Reinforcement Learning Matthew Thomas Jackson, Uljad Berdica, Jarek Luca Liesen, Shimon Whiteson, Jakob Nicolaus Foerster

ICML 2025 ADIOS: Antibody Development via Opponent Shaping Sebastian Rene Towers, Aleksandra Kalisz, Philippe A. Robert, Alicia Higueruelo, Francesca Vianello, Chloe Ming-Han Tsai, Harrison Steel, Jakob Nicolaus Foerster

NeurIPS 2025 AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-Bench Edan Toledo, Karen Hambardzumyan, Martin Josifoski, Rishi Hazra, Nicolas Baldwin, Alexis Audran-Reiss, Michael Kuchnik, Despoina Magka, Minqi Jiang, Alisia Maria Lupidi, Andrei Lupu, Roberta Raileanu, Tatiana Shavrina, Kelvin Niu, Jean-Christophe Gagnon-Audet, Michael Shvartsman, Shagun Sodhani, Alexander H Miller, Abhishek Charnalia, Derek Dunfield, Carole-Jean Wu, Pontus Stenetorp, Nicola Cancedda, Jakob Nicolaus Foerster, Yoram Bachrach

ICML 2025 Ad-Hoc Human-AI Coordination Challenge Tin Dizdarević, Ravi Hammond, Tobias Gessler, Anisoara Calinescu, Jonathan Cook, Matteo Gallici, Andrei Lupu, Jakob Nicolaus Foerster

ICLRW 2025 AgentBreeder: Mitigating the AI Safety Impact of Multi-Agent Scaffolds via Self-Improvement J Rosser, Jakob Nicolaus Foerster

NeurIPS 2025 AgentBreeder: Mitigating the AI Safety Risks of Multi-Agent Scaffolds via Self-Improvement J Rosser, Jakob Nicolaus Foerster

ICLR 2025 BALROG: Benchmarking Agentic LLM and VLM Reasoning on Games Davide Paglieri, Bartłomiej Cupiał, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Łukasz Kuciński, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel

ICLR 2025 Expected Return Symmetries Darius Muglich, Johannes Forkel, Elise van der Pol, Jakob Nicolaus Foerster

NeurIPS 2025 Imagined Autocurricula Ahmet H. Güzel, Matthew Thomas Jackson, Jarek Luca Liesen, Tim Rocktäschel, Jakob Nicolaus Foerster, Ilija Bogunovic, Jack Parker-Holder

NeurIPS 2025 Improving Regret Approximation for Unsupervised Dynamic Environment Generation Harry Mead, Bruno Lacerda, Jakob Nicolaus Foerster, Nick Hawes

ICLR 2025 Kinetix: Investigating the Training of General Agents Through Open-Ended Physics-Based Control Tasks Michael Matthews, Michael Beukman, Chris Lu, Jakob Nicolaus Foerster

NeurIPS 2025 LILO: Learning to Reason at the Frontier of Learnability Thomas Foster, Anya Sims, Johannes Forkel, Jakob Nicolaus Foerster

ICML 2025 LOB-Bench: Benchmarking Generative AI for Finance - An Application to Limit Order Book Data Peer Nagy, Sascha Yves Frey, Kang Li, Bidipta Sarkar, Svitlana Vyetrenko, Stefan Zohren, Ani Calinescu, Jakob Nicolaus Foerster

NeurIPS 2025 Measuring What Matters: Construct Validity in Large Language Model Benchmarks Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou, Franziska Sofia Hafner, Harry Mayne, Jan Batzner, Negar Foroutan, Chris Schmitz, Karolina Korgul, Hunar Batra, Oishi Deb, Emma Beharry, Cornelius Emde, Thomas Foster, Anna Gausen, María Grandury, Simeng Han, Valentin Hofmann, Lujain Ibrahim, Hazel Kim, Hannah Rose Kirk, Fangru Lin, Gabrielle Kaili-May Liu, Lennart Luettgau, Jabez Magomere, Jonathan Rystrøm, Anna Sotnikova, Yushi Yang, Yilun Zhao, Adel Bibi, Antoine Bosselut, Ronald Clark, Arman Cohan, Jakob Nicolaus Foerster, Yarin Gal, Scott A. Hale, Inioluwa Deborah Raji, Christopher Summerfield, Philip Torr, Cozmin Ududec, Luc Rocher, Adam Mahdi

NeurIPS 2025 Meta-Learning Objectives for Preference Optimization Carlo Alfano, Silvia Sapora, Jakob Nicolaus Foerster, Patrick Rebeschini, Yee Whye Teh

ICLR 2025 OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination Tobias Gessler, Tin Dizdarevic, Ani Calinescu, Benjamin Ellis, Andrei Lupu, Jakob Nicolaus Foerster

ICLR 2025 Simplifying Deep Temporal Difference Learning Matteo Gallici, Mattie Fellows, Benjamin Ellis, Bartomeu Pou, Ivan Masmitja, Jakob Nicolaus Foerster, Mario Martin

ICLRW 2025 Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources Alisia Maria Lupidi, Carlos Gemmell, Nicola Cancedda, Jane Yu, Jason E Weston, Jakob Nicolaus Foerster, Roberta Raileanu, Maria Lomeli

ICLRW 2025 StochasTok: Improving Fine-Grained Subword Understanding in LLMs Anya Sims, Cong Lu, Klara Kaleb, Jakob Nicolaus Foerster, Yee Whye Teh

ICLRW 2025 Symmetry-Breaking Augmentations for Ad Hoc Teamwork Ravi Hammond, Dustin Craggs, Mingyu Guo, Jakob Nicolaus Foerster, Ian Reid

NeurIPS 2025 The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements Bingchen Zhao, Despoina Magka, Minqi Jiang, Xian Li, Roberta Raileanu, Tatiana Shavrina, Jean-Christophe Gagnon-Audet, Kelvin Niu, Shagun Sodhani, Michael Shvartsman, Andrei Lupu, Alisia Maria Lupidi, Karen Hambardzumyan, Martin Josifoski, Edan Toledo, Thomas Foster, Lucia Cipolina-Kun, Derek Dunfield, Abhishek Charnalia, Alexander H Miller, Oisin Mac Aodha, Jakob Nicolaus Foerster, Yoram Bachrach

ICMLW 2024 BAM! Just like That: Simple and Efficient Parameter Upcycling for Mixture of Experts Qizhen Zhang, Nikolas Gritsch, Dwaraknath Gnaneshwar, Simon Guo, David Cairuz, Bharat Venkitesh, Jakob Nicolaus Foerster, Phil Blunsom, Sebastian Ruder, Ahmet Üstün, Acyr Locatelli

ICLR 2024 Behaviour Distillation Andrei Lupu, Chris Lu, Jarek Luca Liesen, Robert Tjarko Lange, Jakob Nicolaus Foerster

ICMLW 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? Alexander D. Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster

ICML 2024 Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning Michael Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew Thomas Jackson, Samuel Coward, Jakob Nicolaus Foerster

ICMLW 2024 DARE: The Deep Adaptive Regulator for Control of Uncertain Continuous-Time Systems Harrison Waldon, Fayçal Drissi, Yannick Limmer, Uljad Berdica, Jakob Nicolaus Foerster, Alvaro Cartea

ICMLW 2024 Discovering Preference Optimization Algorithms with and for Large Language Models Chris Lu, Samuel Holt, Claudio Fanconi, Alex James Chan, Jakob Nicolaus Foerster, Mihaela van der Schaar, Robert Tjarko Lange

ICLR 2024 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

ICML 2024 EvIL: Evolution Strategies for Generalisable Imitation Learning Silvia Sapora, Gokul Swamy, Chris Lu, Yee Whye Teh, Jakob Nicolaus Foerster

TMLR 2024 Foundational Challenges in Assuring Alignment and Safety of Large Language Models Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, Jose Hernandez-Orallo, Lewis Hammond, Eric J Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Chenyu Zhang, Ruiqi Zhong, Sean O hEigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schroeder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger

ICMLW 2024 Higher Order and Self-Referential Evolution for Population-Based Methods Samuel Coward, Chris Lu, Alistair Letcher, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster

ICLR 2024 Illusory Attacks: Information-Theoretic Detectability Matters in Adversarial Attacks Tim Franzmeyer, Stephen Marcus McAleer, Joao F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schroeder de Witt

ICMLW 2024 Jafar: An Open-Source Genie Reimplemention in JAX Timon Willi, Matthew Thomas Jackson, Jakob Nicolaus Foerster

ICLR 2024 Learning Multi-Agent Communication with Contrastive Learning Yat Long Lo, Biswa Sengupta, Jakob Nicolaus Foerster, Michael Noukhovitch

NeurIPS 2024 Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence Rakshit S Trivedi, Akbir Khan, Jesse Clifton, Lewis Hammond, Edgar A. Duéñez-Guzmán, John P Agapiou, Jayd Matyas, Sasha Vezhnevets, Dipam Chakraborty, Yue Zhao, Marko Tesic, Barna Pásztor, Yunke Ao, Omar G. Younis, Jiawei Huang, Benjamin Swain, Haoyuan Qin, Mian Deng, Ziwei Deng, Utku Erdoğanaras, Natasha Jaques, Jakob Nicolaus Foerster, Vincent Conitzer, Jose Hernandez-Orallo, Dylan Hadfield-Menell, Joel Z Leibo

ICML 2024 Mixtures of Experts Unlock Parameter Scaling for Deep RL Johan Samir Obando Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro

NeurIPSW 2024 On Reward Functions for Self-Improving Chain-of-Thought Reasoning Without Supervised Datasets (Abridged Version) Thomas Foster, Eltayeb Ahmed, Jonathan Cook, Shalev Lifshitz, Tim Rocktäschel, Jakob Nicolaus Foerster

ICML 2024 PARDEN, Can You Repeat That? Defending Against Jailbreaks via Repetition Ziyang Zhang, Qizhen Zhang, Jakob Nicolaus Foerster

ICML 2024 Position: Near to Mid-Term Risks and Opportunities of Open-Source Generative AI Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder De Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Rottger, Philip Torr, Trevor Darrell, Yong Suk Lee, Jakob Nicolaus Foerster

ICLRW 2024 Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H. Markosyan, Manish Bhatt, Yuning Mao, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster, Tim Rocktäschel, Roberta Raileanu

ICML 2024 ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages Andrew Jesson, Chris Lu, Gunshi Gupta, Nicolas Beltran-Velez, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal

ICML 2024 Refining Minimax Regret for Unsupervised Environment Design Michael Beukman, Samuel Coward, Michael Matthews, Mattie Fellows, Minqi Jiang, Michael D Dennis, Jakob Nicolaus Foerster

NeurIPSW 2024 Robust Offline Learning via Adversarial World Models Uljad Berdica, Kelvin Li, Michael Beukman, Alexander David Goldie, Perla Maiolino, Jakob Nicolaus Foerster

ICLR 2024 Select to Perfect: Imitating Desired Behavior from Large Multi-Agent Data Tim Franzmeyer, Edith Elkind, Philip Torr, Jakob Nicolaus Foerster, Joao F. Henriques

NeurIPSW 2024 TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generation Jonathan Cook, Tim Rocktäschel, Jakob Nicolaus Foerster, Dennis Aumiller, Alex Wang

NeurIPSW 2024 Track 1: Robust Offline Learning via Adversarial World Models Uljad Berdica, Kelvin Li, Michael Beukman, Alexander David Goldie, Perla Maiolino, Jakob Nicolaus Foerster

ICML 2023 Adversarial Cheap Talk Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

ICLR 2023 Adversarial Diversity in Hanabi Brandon Cui, Andrei Lupu, Samuel Sokota, Hengyuan Hu, David J Wu, Jakob Nicolaus Foerster

ICMLW 2023 Analyzing the Sample Complexity of Model-Free Opponent Shaping Kitty Fung, Qizhen Zhang, Chris Lu, Timon Willi, Jakob Nicolaus Foerster

ICLR 2023 Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning Yat Long Lo, Christian Schroeder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson

NeurIPSW 2023 Discovering Temporally-Aware Reinforcement Learning Algorithms Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster

ICMLW 2023 Illusory Attacks: Detectability Matters in Adversarial Attacks on Sequential Decision-Makers Tim Franzmeyer, Stephen Marcus McAleer, Joao F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schroeder de Witt

NeurIPSW 2023 JaxMARL: Multi-Agent RL Environments in JAX Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Nicolaus Foerster

ICML 2023 Learning Intuitive Policies Using Action Features Mingwei Ma, Jizhou Liu, Samuel Sokota, Max Kleiman-Weiner, Jakob Nicolaus Foerster

TMLR 2023 Learning to Optimize Quasi-Newton Methods Isaac Liao, Rumen Dangovski, Jakob Nicolaus Foerster, Marin Soljacic

ICLR 2023 MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning Mikayel Samvelyan, Akbir Khan, Michael D Dennis, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster, Roberta Raileanu, Tim Rocktäschel

NeurIPSW 2023 Noisy ZSC: Breaking the Common Knowledge Assumption in Zero-Shot Coordination Games Usman Anwar, Jia Wan, David Krueger, Jakob Nicolaus Foerster

ICLR 2023 Perfectly Secure Steganography Using Minimum Entropy Coupling Christian Schroeder de Witt, Samuel Sokota, J Zico Kolter, Jakob Nicolaus Foerster, Martin Strohmeier

ICMLW 2023 Structured State Space Models for In-Context Reinforcement Learning Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Nicolaus Foerster, Satinder Singh, Feryal Behbahani

ICMLW 2023 Who to Imitate: Imitating Desired Behavior from Diverse Multi-Agent Datasets Tim Franzmeyer, Jakob Nicolaus Foerster, Edith Elkind, Philip Torr, Joao F. Henriques

ICLR 2022 A Fine-Tuning Approach to Belief State Modeling Samuel Sokota, Hengyuan Hu, David J Wu, J Zico Kolter, Jakob Nicolaus Foerster, Noam Brown

ICMLW 2022 Adversarial Cheap Talk Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

NeurIPSW 2022 Adversarial Cheap Talk Chris Lu, Timon Willi, Alistair Letcher, Jakob Nicolaus Foerster

ICMLW 2022 Discovered Policy Optimisation Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schroeder de Witt, Jakob Nicolaus Foerster

NeurIPSW 2022 Human-AI Coordination via Human-Regularized Search and Learning Hengyuan Hu, David J Wu, Adam Lerer, Jakob Nicolaus Foerster, Noam Brown

ICLRW 2022 Influencing Long-Term Behavior in Multiagent Reinforcement Learning Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob Nicolaus Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P How

NeurIPSW 2022 MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning Mikayel Samvelyan, Akbir Khan, Michael D Dennis, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster, Roberta Raileanu, Tim Rocktäschel

ICLRW 2022 Model-Free Opponent Shaping Chris Lu, Timon Willi, Christian Schroeder de Witt, Jakob Nicolaus Foerster

NeurIPSW 2021 Grounding Aleatoric Uncertainty in Unsupervised Environment Design Minqi Jiang, Michael D Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Kuttler, Edward Grefenstette, Tim Rocktäschel, Jakob Nicolaus Foerster

NeurIPSW 2021 No DICE: An Investigation of the Bias-Variance Tradeoff in Meta-Gradients Risto Vuorio, Jacob Austin Beck, Gregory Farquhar, Jakob Nicolaus Foerster, Shimon Whiteson

NeurIPSW 2021 That Escalated Quickly: Compounding Complexity by Editing Levels at the Frontier of Agent Capabilities Jack Parker-Holder, Minqi Jiang, Michael D Dennis, Mikayel Samvelyan, Jakob Nicolaus Foerster, Edward Grefenstette, Tim Rocktäschel