46 citations · 85 across the 8 of their papers we have counts for
8 papers
Long-Pulse Laser-Induced Cavitation: A Race Between Advection and Phase Transition
Xuning Zhao, Wentao Ma, Junqin Chen +3
Vapor bubbles generated by long-pulsed laser often have complex non-spherical shapes that reflect some characteristics (e.g., direction, width) of the laser beam. The transition be…
KECRS: Towards Knowledge-Enriched Conversational Recommendation System
Tong Zhang, Yong Liu, Peixiang Zhong +3
The chit-chat-based conversational recommendation systems (CRS) provide item recommendations to users through natural language interactions. To better understand user's intentions,…
Keyword-Guided Neural Conversational Model
Peixiang Zhong, Yong Liu, Hao Wang +1
We study the problem of imposing conversational goals/keywords on open-domain conversational agents, where the agent is required to lead the conversation to a target keyword smooth…
CARE: Commonsense-Aware Emotional Response Generation with Latent Concepts
Peixiang Zhong, Di Wang, Pengfei Li +3
Rationality and emotion are two fundamental elements of humans. Endowing agents with rationality and emotion has been one of the major milestones in AI. However, in the field of co…
Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations
Peixiang Zhong, Di Wang, Chunyan Miao
Messages in human conversations inherently convey emotions. The task of detecting emotions in textual conversations leads to a wide range of applications such as opinion mining in…
EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
Peixiang Zhong, Di Wang, Chunyan Miao
Electroencephalography (EEG) measures the neuronal activities in different brain regions via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit…
ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNN
Peixiang Zhong, Chunyan Miao
In this paper we present our model on the task of emotion detection in textual conversations in SemEval-2019. Our model extends the Recurrent Convolutional Neural Network (RCNN) by…
An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss
Peixiang Zhong, Di Wang, Chunyan Miao
Affect conveys important implicit information in human communication. Having the capability to correctly express affect during human-machine conversations is one of the major miles…