45 citations · 49 across the 6 of their papers we have counts for
6 papers
Greedy based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning
Lipeng Wan, Zeyang Liu, Xingyu Chen +2
Due to the representation limitation of the joint Q value function, multi-agent reinforcement learning methods with linear value decomposition (LVD) or monotonic value decompositio…
SeSQL: Yet Another Large-scale Session-level Chinese Text-to-SQL Dataset
Saihao Huang, Lijie Wang, Zhenghua Li +6
As the first session-level Chinese dataset, CHASE contains two separate parts, i.e., 2,003 sessions manually constructed from scratch (CHASE-C), and 3,456 sessions translated from…
Multi-Agent Intention Sharing via Leader-Follower Forest
Zeyang Liu, Lipeng Wan, Xue sui +2
Intention sharing is crucial for efficient cooperation under partially observable environments in multi-agent reinforcement learning (MARL). However, message deceiving, i.e., a mis…
Greedy-based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning
Lipeng Wan, Zeyang Liu, Xingyu Chen +2
Due to the representation limitation of the joint Q value function, multi-agent reinforcement learning methods with linear value decomposition (LVD) or monotonic value decompositio…
POSSCORE: A Simple Yet Effective Evaluation of Conversational Search with Part of Speech Labelling
Zeyang Liu, Ke Zhou, Jiaxin Mao +1
Conversational search systems, such as Google Assistant and Microsoft Cortana, provide a new search paradigm where users are allowed, via natural language dialogues, to communicate…
Meta-evaluation of Conversational Search Evaluation Metrics
Zeyang Liu, Ke Zhou, Max L. Wilson
Conversational search systems, such as Google Assistant and Microsoft Cortana, enable users to interact with search systems in multiple rounds through natural language dialogues. E…