500 citations · 1.6k across the 68 of their papers we have counts for
15 papers · 1 filter
The JDDC Corpus: A Large-Scale Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service
Meng Chen, Ruixue Liu, Lei Shen +5
Human conversations are complicated and building a human-like dialogue agent is an extremely challenging task. With the rapid development of deep learning techniques, data-driven m…
Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding
Yun Tang, Jing Huang, Guangtao Wang +2
Translational distance-based knowledge graph embedding has shown progressive improvements on the link prediction task, from TransE to the latest state-of-the-art RotatE. However, N…
Multimodal Intelligence: Representation Learning, Information Fusion, and Applications
Chao Zhang, Zichao Yang, Xiaodong He +1
Deep learning methods have revolutionized speech recognition, image recognition, and natural language processing since 2010. Each of these tasks involves a single modality in their…
Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents
Ming Tu, Kevin Huang, Guangtao Wang +3
Interpretable multi-hop reading comprehension (RC) over multiple documents is a challenging problem because it demands reasoning over multiple information sources and explaining th…
Relation Module for Non-answerable Prediction on Question Answering
Kevin Huang, Yun Tang, Jing Huang +2
Machine reading comprehension(MRC) has attracted significant amounts of research attention recently, due to an increase of challenging reading comprehension datasets. In this paper…
Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification
Xiaochen Hou, Jing Huang, Guangtao Wang +2
Aspect-level sentiment classification aims to identify the sentiment polarity towards a specific aspect term in a sentence. Most current approaches mainly consider the semantic inf…
Zero-shot Text-to-SQL Learning with Auxiliary Task
Shuaichen Chang, Pengfei Liu, Yun Tang +3
Recent years have seen great success in the use of neural seq2seq models on the text-to-SQL task. However, little work has paid attention to how these models generalize to realisti…
Mappa Mundi: An Interactive Artistic Mind Map Generator with Artificial Imagination
Ruixue Liu, Baoyang Chen, Meng Chen +3
We present a novel real-time, collaborative, and interactive AI painting system, Mappa Mundi, for artistic Mind Map creation. The system consists of a voice-based input interface,…
Multiple instance learning with graph neural networks
Ming Tu, Jing Huang, Xiaodong He +1
Multiple instance learning (MIL) aims to learn the mapping between a bag of instances and the bag-level label. In this paper, we propose a new end-to-end graph neural network (GNN)…
Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs
Ming Tu, Guangtao Wang, Jing Huang +3
Multi-hop reading comprehension (RC) across documents poses new challenge over single-document RC because it requires reasoning over multiple documents to reach the final answer. I…
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations
Fenglin Liu, Yuanxin Liu, Xuancheng Ren +2
In vision-and-language grounding problems, fine-grained representations of the image are considered to be of paramount importance. Most of the current systems incorporate visual fe…
Towards adversarial learning of speaker-invariant representation for speech emotion recognition
Ming Tu, Yun Tang, Jing Huang +2
Speech emotion recognition (SER) has attracted great attention in recent years due to the high demand for emotionally intelligent speech interfaces. Deriving speaker-invariant repr…
From Knowledge Map to Mind Map: Artificial Imagination
Ruixue Liu, Baoyang Chen, Xiaoyu Guo +4
Imagination is one of the most important factors which makes an artistic painting unique and impressive. With the rapid development of Artificial Intelligence, more and more resear…
Object-driven Text-to-Image Synthesis via Adversarial Training
Wenbo Li, Pengchuan Zhang, Lei Zhang +4
In this paper, we propose Object-driven Attentive Generative Adversarial Newtorks (Obj-GANs) that allow object-centered text-to-image synthesis for complex scenes. Following the tw…
Deep Speaker Embedding Learning with Multi-Level Pooling for Text-Independent Speaker Verification
Yun Tang, Guohong Ding, Jing Huang +2
This paper aims to improve the widely used deep speaker embedding x-vector model. We propose the following improvements: (1) a hybrid neural network structure using both time delay…