219 citations · 448 across the 14 of their papers we have counts for
14 papers
STCF Conceptual Design Report: Volume 1 -- Physics & Detector
M. Achasov, X. C. Ai, R. Aliberti +424
The Super -Charm facility (STCF) is an electron-positron collider proposed by the Chinese particle physics community. It is designed to operate in a center-of-mass energy range…
Energy Dependence of Intermittency for Charged Hadrons in Au+Au Collisions at RHIC
STAR Collaboration, M. I. Abdulhamid, B. E. Aboona +364
Density fluctuations near the QCD critical point can be probed via an intermittency analysis in relativistic heavy-ion collisions. We report the first measurement of intermittency…
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation
Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao +5
Building models of natural language processing (NLP) is challenging in low-resource scenarios where only limited data are available. Optimization-based meta-learning algorithms ach…
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…
Trivial bundle embeddings for learning graph representations
Zheng Xie, Xiaojing Zuo, Yiping Song
Embedding real-world networks presents challenges because it is not clear how to identify their latent geometries. Embedding some disassortative networks, such as scale-free networ…
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…
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…
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…
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications
Zequn Liu, Ruiyi Zhang, Yiping Song +2
Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning method, is successfully employed in NLP applications including few-shot text classification and multi-domain low…
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…
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…
Two are Better than One: An Ensemble of Retrieval- and Generation-Based Dialog Systems
Yiping Song, Rui Yan, Xiang Li +2
Open-domain human-computer conversation has attracted much attention in the field of NLP. Contrary to rule- or template-based domain-specific dialog systems, open-domain conversati…
Dialogue Session Segmentation by Embedding-Enhanced TextTiling
Yiping Song, Lili Mou, Rui Yan +4
In human-computer conversation systems, the context of a user-issued utterance is particularly important because it provides useful background information of the conversation. Howe…
Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation
Lili Mou, Yiping Song, Rui Yan +3
Using neural networks to generate replies in human-computer dialogue systems is attracting increasing attention over the past few years. However, the performance is not satisfactor…