Optimization of image description metrics using policy gradient methods. - Siqi Liu 002; Zhenhai Zhu; Ning Ye; Sergio Guadarrama; Kevin Murphy 002 (CoRR, 2016)

Improved Image Captioning via Policy Gradient optimization of SPIDEr. - Siqi Liu 002; Zhenhai Zhu; Ning Ye; Sergio Guadarrama; Kevin Murphy 002 (ICCV, 2017)

The Body is Not a Given: Joint Agent Policy Learning and Morphology Evolution. - Dylan Banarse; Yoram Bachrach; Siqi Liu 002; Guy Lever; Nicolas Heess; Chrisantha Fernando; Pushmeet Kohli; Thore Graepel (AAMAS, 2019)

Observational Learning by Reinforcement Learning. - Diana Borsa; Nicolas Heess; Bilal Piot; Siqi Liu 002; Leonard Hasenclever; Rémi Munos; Olivier Pietquin (AAMAS, 2019)

Emergent Coordination Through Competition. - Siqi Liu 002; Guy Lever; Josh Merel; Saran Tunyasuvunakool; Nicolas Heess; Thore Graepel (ICLR (Poster), 2019)

Hierarchical Visuomotor Control of Humanoids. - Josh Merel; Arun Ahuja; Vu Pham; Saran Tunyasuvunakool; Siqi Liu 002; Dhruva Tirumala; Nicolas Heess; Greg Wayne (ICLR (Poster), 2019)

Reinforcement Learning Agents acquire Flocking and Symbiotic Behaviour in Simulated Ecosystems. - Peter Sunehag; Guy Lever; Siqi Liu 002; Josh Merel; Nicolas Heess; Joel Z. Leibo; Edward Hughes 001; Tom Eccles; Thore Graepel (ALIFE, 2019)

A Generalized Training Approach for Multiagent Learning. - Paul Muller; Shayegan Omidshafiei; Mark Rowland 001; Karl Tuyls; Julien Pérolat; Siqi Liu 002; Daniel Hennes; Luke Marris; Marc Lanctot; Edward Hughes 001; Zhe Wang 055; Guy Lever; et al. (ICLR, 2020)

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 002; Dhruva Tirumala; Nicolas Heess; Dan Belov; et al. (ICLR, 2020)

dm_control: Software and tasks for continuous control. - Saran Tunyasuvunakool; Alistair Muldal; Yotam Doron; Siqi Liu 002; Steven Bohez; Josh Merel; Tom Erez; Timothy P. Lillicrap; Nicolas Heess; Yuval Tassa (Softw. Impacts, 2020)

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. - Marta Garnelo; Wojciech Marian Czarnecki; Siqi Liu 002; Dhruva Tirumala; Junhyuk Oh; Gauthier Gidel; Hado van Hasselt; David Balduzzi (AAMAS, 2021)

Launchpad: A Programming Model for Distributed Machine Learning Research. - Fan Yang; Gabriel Barth-Maron; Piotr Stanczyk; Matthew W. Hoffman; Siqi Liu 002; Manuel Kroiss; Aedan Pope; Alban Rrustemi (CoRR, 2021)

NeuPL: Neural Population Learning. - Siqi Liu 002; Luke Marris; Daniel Hennes; Josh Merel; Nicolas Heess; Thore Graepel (ICLR, 2022)

Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games. - Siqi Liu 002; Marc Lanctot; Luke Marris; Nicolas Heess (ICML, 2022)

Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers. - Luke Marris; Ian Gemp; Thomas Anthony 001; Andrea Tacchetti; Siqi Liu 002; Karl Tuyls (NeurIPS, 2022)

Developing, evaluating and scaling learning agents in multi-agent environments. - Ian Gemp; Thomas W. Anthony 001; Yoram Bachrach; Avishkar Bhoopchand; Kalesha Bullard; Jerome T. Connor; Vibhavari Dasagi; Bart De Vylder; Edgar A. Duéñez-Guzmán; Romuald Elie; Richard Everett 001; Daniel Hennes; et al. (AI Commun., 2022)

Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. - Bobak Shahriari; Abbas Abdolmaleki; Arunkumar Byravan; Abe Friesen; Siqi Liu 002; Jost Tobias Springenberg; Nicolas Heess; Matt Hoffman 001; Martin A. Riedmiller (CoRR, 2022)

From motor control to team play in simulated humanoid football. - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech M. Czarnecki; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Sci. Robotics, 2022)

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech Czarnecki 001; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Zenodo, 2022)

Neural Population Learning beyond Symmetric Zero-Sum Games. - Siqi Liu 002; Luke Marris; Marc Lanctot; Georgios Piliouras; Joel Z. Leibo; Nicolas Heess (AAMAS, 2024)

NfgTransformer: Equivariant Representation Learning for Normal-form Games. - Siqi Liu 002; Luke Marris; Georgios Piliouras; Ian Gemp; Nicolas Heess (ICLR, 2024)

States as Strings as Strategies: Steering Language Models with Game-Theoretic Solvers. - Ian Gemp; Yoram Bachrach; Marc Lanctot; Roma Patel; Vibhavari Dasagi; Luke Marris; Georgios Piliouras; Siqi Liu 002; Karl Tuyls (CoRR, 2024)

Visualizing 2x2 Normal-Form Games: twoxtwogame LaTeX Package. - Luke Marris; Ian Gemp; Siqi Liu 002; Joel Z. Leibo; Georgios Piliouras (CoRR, 2024)

Convex Markov Games: A Framework for Fairness, Imitation, and Creativity in Multi-Agent Learning. - Ian Gemp; Andreas Haupt; Luke Marris; Siqi Liu 002; Georgios Piliouras (CoRR, 2024)

Re-evaluating Open-ended Evaluation of Large Language Models. - Siqi Liu 002; Ian Gemp; Luke Marris; Georgios Piliouras; Nicolas Heess; Marc Lanctot (ICLR, 2025)

Deviation Ratings: A General, Clone-Invariant Rating Method. - Luke Marris; Siqi Liu 002; Ian Gemp; Georgios Piliouras; Marc Lanctot (CoRR, 2025)