papers

Publications (29)

cs.AI2024

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Chris Lu, Cong Lu, Robert Tjarko Lange +3

cs.LG2022

Bayesian Generational Population-Based Training

Xingchen Wan, Cong Lu, Jack Parker-Holder +4

cs.LG2023

Synthetic Experience Replay

Cong Lu, Philip J. Ball, Yee Whye Teh +1

cs.AI2026

Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents

Jenny Zhang, Shengran Hu, Cong Lu +2

cs.AI2025

Automated Design of Agentic Systems

Shengran Hu, Cong Lu, Jeff Clune

cs.AI2025

SIMA 2: A Generalist Embodied Agent for Virtual Worlds

SIMA team, Adrian Bolton, Alexander Lerchner +63

cs.AI2025

The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

Yutaro Yamada, Robert Tjarko Lange, Cong Lu +5

cs.CV2024

Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control

Gunshi Gupta, Karmesh Yadav, Yarin Gal +4

cs.LG2025

Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models

Cong Lu, Shengran Hu, Jeff Clune

cond-mat.mtrl-sci2016

Elementary specific spin and orbital moments of ultrathin CoFeB amorphous films on GaAs(100)

Yu Yan, Cong Lu, Hongqing Tu +12

cond-mat.mtrl-sci2025

Incipient ionic conductors: Ion-constrained lattices achieving superionic-like thermal conductivity by extreme anharmonicity

Yongheng Li, Chunqiu Lu, Bin Wei +7

cs.AI2022

Go-Explore Complex 3D Game Environments for Automated Reachability Testing

Cong Lu, Raluca Georgescu, Johan Verwey

cs.LG2021

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment

Philip J. Ball, Cong Lu, Jack Parker-Holder +1

cs.LG2022

Revisiting Design Choices in Offline Model-Based Reinforcement Learning

Cong Lu, Philip J. Ball, Jack Parker-Holder +2

cs.LG2025

Automated Capability Discovery via Foundation Model Self-Exploration

Cong Lu, Shengran Hu, Jeff Clune

cs.LG2025

Foundation Model Self-Play: Open-Ended Strategy Innovation via Foundation Models

Aaron Dharna, Cong Lu, Jeff Clune

cs.CL2026

SkillCraft: Can LLM Agents Learn to Use Tools Skillfully?

Shiqi Chen, Jingze Gai, Ruochen Zhou +13

cs.RO2025

IGDrivSim: A Benchmark for the Imitation Gap in Autonomous Driving

Clémence Grislain, Risto Vuorio, Cong Lu +1

cs.LG2021

Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning

Luisa Zintgraf, Leo Feng, Cong Lu +4

cs.AI2026

Towards End-to-End Automation of AI Research

Yutaro Yamada, Robert Tjarko Lange, Cong Lu +5

cs.LG2024

The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

Anya Sims, Cong Lu, Jakob Foerster +1

cs.LG2024

Policy-Guided Diffusion

Matthew Thomas Jackson, Michael Tryfan Matthews, Cong Lu +3

stat.ML2021

Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces

Xingchen Wan, Vu Nguyen, Huong Ha +3

cs.LG2024

A Bayesian Solution To The Imitation Gap

Risto Vuorio, Mattie Fellows, Cong Lu +2

cs.CV2024

Video Diffusion Models: A Survey

Andrew Melnik, Michal Ljubljanac, Cong Lu +3

cs.LG2023

Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations

Cong Lu, Philip J. Ball, Tim G. J. Rudner +3

cs.LG2022

On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations

Tim G. J. Rudner, Cong Lu, Michael A. Osborne +2

cs.AI2026

AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery

Guiyao Tie, Jiawen Shi, Dingjie Song +20

cs.CL2026

StochasTok: Improving Fine-Grained Subword Understanding in LLMs

Anya Sims, Thom Foster, Klara Kaleb +5