activity
20172022
most citedACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning

39 citations · 49 across the 5 of their papers we have counts for

collaborators

6 papers

nucl-ex2022

Observation of the -bond linear-chain molecular structure in C

J. X. Han, Y. Liu, Y. L. Ye +37

Measurements of the H(C,CHe+Be or He+Be)H inelastic excitation and cluster-decay reactions have been carried out at a b…

cs.CL2020

Response-Anticipated Memory for On-Demand Knowledge Integration in Response Generation

Zhiliang Tian, Wei Bi, Dongkyu Lee +4

Neural conversation models are known to generate appropriate but non-informative responses in general. A scenario where informativeness can be significantly enhanced is Conversing…

cs.LG202010 cited

Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases

Luchen Liu, Zequn Liu, Haoxian Wu +4

Mortality prediction of diverse rare diseases using electronic health record (EHR) data is a crucial task for intelligent healthcare. However, data insufficiency and the clinical d…

physics.optics2020

Improved mathematical models of structured-light modulation analysis technique for contaminant and defect detection

Yiyang Huang, Huimin Yue, Yuyao Fang +2

Surface quality inspection of optical components is critical in optical and electronic industries. Structured-Light Modulation Analysis Technique (SMAT) is a novel method recently…

cs.CL2019

Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks

Yiping Song, Zequn Liu, Wei Bi +2

Training the generative models with minimal corpus is one of the critical challenges for building open-domain dialogue systems. Existing methods tend to use the meta-learning frame…

cs.AI201739 cited

ACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning

Hangyu Mao, Zhibo Gong, Yan Ni +1

Communication is a critical factor for the big multi-agent world to stay organized and productive. Typically, most previous multi-agent "learning-to-communicate" studies try to pre…