10 citations · 11 across the 7 of their papers we have counts for
9 papers
Harnessing Large Language Models to Compile Task-Relevant Context into Bayesian Optimisation
Zhongwei Yu, Sourabh Roy, Bin Cao +3
Incorporating rich task-relevant context, such as domain knowledge and external observations, is a key capability yet remains challenging for Bayesian optimisation (BO). Recently,…
Large Discovery Models: Empirically-grounded Model-Based Open-Ended Search
Zhongwei Yu, Yan Song, Xue Yan +9
Scientific discovery often involves optimising expensive-to-evaluate objectives over vast, structured, and open-ended hypothesis spaces, such as molecules, protein sequences, and c…
Sim2Sea: Sim-to-Real Policy Transfer for Maritime Vessel Navigation in Congested Waters
Xinyu Cui, Xuanfa Jin, Xue Yan +7
Autonomous navigation in congested maritime environments is a critical capability for a wide range of real-world applications. However, it remains an unresolved challenge due to co…
Self-Verifying Reflection Helps Transformers with CoT Reasoning
Zhongwei Yu, Wannian Xia, Xue Yan +4
Advanced large language models (LLMs) frequently reflect in reasoning chain-of-thoughts (CoTs), where they self-verify the correctness of current solutions and explore alternatives…
Memory-Driven Self-Improvement for Decision Making with Large Language Models
Xue Yan, Zijing Ou, Mengyue Yang +4
Large language models (LLMs) have emerged as effective action policies for sequential decision-making (SDM) tasks due to their extensive prior knowledge. However, this broad yet ge…
Efficient Reinforcement Learning with Large Language Model Priors
Xue Yan, Yan Song, Xidong Feng +4
In sequential decision-making (SDM) tasks, methods like reinforcement learning (RL) and heuristic search have made notable advances in specific cases. However, they often require e…
Mean Field Correlated Imitation Learning
Zhiyu Zhao, Qirui Mi, Ning Yang +4
We investigate multi-agent imitation learning (IL) within the framework of mean field games (MFGs), considering the presence of time-varying correlated signals. Existing MFG IL alg…
Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach
Weiyu Ma, Qirui Mi, Yongcheng Zeng +5
StarCraft II is a challenging benchmark for AI agents due to the necessity of both precise micro level operations and strategic macro awareness. Previous works, such as Alphastar a…
Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models
Xue Yan, Yan Song, Xinyu Cui +4
Large language models (LLMs) demonstrate their promise in tackling complicated practical challenges by combining action-based policies with chain of thought (CoT) reasoning. Having…