Re-evaluating Open-Ended Evaluation of Large Language Models

Siqi Liu*, Ian Gemp*, Luke Marris, Georgios Piliouras, Nicolas Heess, Marc Lanctot

ICLR 2025 | paper | demo | code

Deviation Ratings: A General, Clone-Invariant Rating Method

Luke Marris, Siqi Liu, Ian Gemp, Georgios Piliouras, Marc Lanctot

AAMAS Workshop 2025 | paper

NfgTransformer: Equivariant Representation Learning for Normal-form Games

Siqi Liu, Luke Marris, Georgios Piliouras, Ian Gemp, Nicolas Heess

ICLR 2024 | paper | code

Neural Population Learning beyond Symmetric Zero-sum Games

Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess

AAMAS 2024 | paper

States as Strings as Strategies: Steering Language Models with Game-theoretic Solvers

Ian Gemp, Roma Patel, Yoram Bachrach, Marc Lanctot, Vibhavari Dasagi, Luke Marris, Georgios Piliouras, Siqi Liu, Karl Tuyls

ICML Agentic Markets Workshop 2024 | paper

Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers

Luke Marris, Ian Gemp, Thomas Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls

NeurIPS 2022 | paper

Developing, evaluating and scaling learning agents in multi-agent environments

Ian Gemp, Thomas Anthony, Yoram Bachrach, Avishkar Bhoopchand, Kalesha Bullard, Jerome Connor, Vibhavari Dasagi, Bart De Vylder, Edgar A Duéñez-Guzmán, Romuald Elie, Richard Everett, Daniel Hennes, Edward Hughes, Mina Khan, Marc Lanctot, Kate Larson, Guy Lever, Siqi Liu, Luke Marris, Kevin R McKee, Paul Muller, Julien Pérolat, Florian Strub, Andrea Tacchetti, Eugene Tarassov, Zhe Wang, Karl Tuyls

AI Communications 2022 | paper

From Motor Control to Team Play in Simulated Humanoid Football

Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess

Science Robotics 2022 | paper | blog | demo | code

Simplex NeuPL: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games

Siqi Liu, Marc Lanctot, Luke Marris, Nicolas Heess

ICML 2022 | paper | spotlight

NeuPL: Neural Population Learning

Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel

ICLR 2022 | paper | demo | poster

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi

AAMAS 2021 | paper

dm_control: Software and Tasks for Continuous Control

Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, Nicolas Heess, Yuval Tassa

Software Impacts 2020 | paper | code

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

H Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin Riedmiller, Matthew M Botvinick

ICLR 2020 | paper

A Generalized Training Approach for Multiagent Learning

Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Perolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Remi Munos

ICLR 2020 | paper

Emergent Coordination through Competition

Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel

ICLR 2019 | paper | website | code

Hierarchical Visuomotor Control of Humanoids

Josh Merel, Arun Ahuja, Vu Pham, Saran Tunyasuvunakool, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Greg Wayne

ICLR 2019 | paper | demo

dm_env: a Python interface for reinforcement learning environments

Alistair Muldal, Yotam Doron, John Aslanides, Tim Harley, Tom Ward, Siqi Liu

github 2019 | code

Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems

Peter Sunehag, Guy Lever, Siqi Liu, Josh Merel, Nicolas Heess, Joel Z Leibo, Edward Hughes, Tom Eccles, Thore Graepel

ALIFE 2019 | paper

The Body is not a Given: Joint Agent Policy Learning and Morphology Evolution

Dylan Banarse, Yoram Bachrach, Siqi Liu, Chrisantha Fernando, Nicolas Heess, Pushmeet Kohli, Guy Lever, Thore Graepel

AAMAS 2019 | paper

Observational Learning by Reinforcement Learning

Diana Borsa, Nicolas Heess, Bilal Piot, Siqi Liu, Leonard Hasenclever, Remi Munos, Olivier Pietquin

AAMAS 2019 | paper

Improved Image Captioning via Policy Gradient Optimization of SPIDER

Siqi Liu, Zhenhai Zhu, Ning Ye, Sergio Guadarrama, Kevin Murphy

ICCV 2017 | paper | oral