83 citations · 114 across the 23 of their papers we have counts for
7 papers · 1 filter
Sequence Pathfinder for Multi-Agent Pickup and Delivery in the Warehouse
Zeyuan Zhao, Chaoran Li, Shao Zhang +1
Multi-Agent Pickup and Delivery (MAPD) is a challenging extension of Multi-Agent Path Finding (MAPF), where agents are required to sequentially complete tasks with fixed-location p…
Context Value Informed In-Context Reinforcement Learning
Wenhao Zhang, Shao Zhang, Xihuai Wang +2
In-context reinforcement learning (ICRL) has emerged as an effective paradigm for test time adaptation to unseen tasks without parameter updates. However, existing ICRL methods can…
Structured In-context Environment Scaling for Large Language Model Reasoning
Peng Yu, Zeyuan Zhao, Shao Zhang +3
Large language models (LLMs) have achieved significant advancements in reasoning capabilities through reinforcement learning (RL) via environmental exploration. As the intrinsic pr…
Audio Turing Test: Benchmarking the Human-likeness of Large Language Model-based Text-to-Speech Systems in Chinese
Xihuai Wang, Ziyi Zhao, Siyu Ren +9
Recent advances in large language models (LLMs) have significantly improved text-to-speech (TTS) systems, enhancing control over speech style, naturalness, and emotional expression…
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning
Kun Hu, Muning Wen, Xihuai Wang +5
Multi-agent reinforcement learning (MARL) faces challenges in coordinating agents due to complex interdependencies within multi-agent systems. Most MARL algorithms use the simultan…
Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration
Shao Zhang, Xihuai Wang, Wenhao Zhang +10
Agents built on large language models (LLMs) have excelled in turn-by-turn human-AI collaboration but struggle with simultaneous tasks requiring real-time interaction. Latency issu…
Language Games as the Pathway to Artificial Superhuman Intelligence
Ying Wen, Ziyu Wan, Shao Zhang
The evolution of large language models (LLMs) toward artificial superhuman intelligence (ASI) hinges on data reproduction, a cyclical process in which models generate, curate and r…