28 citations · 99 across the 9 of their papers we have counts for
9 papers
Cross-modal Contrastive Distillation for Instructional Activity Anticipation
Zhengyuan Yang, Jingen Liu, Jing Huang +4
In this study, we aim to predict the plausible future action steps given an observation of the past and study the task of instructional activity anticipation. Unlike previous antic…
Speaker-invariant Affective Representation Learning via Adversarial Training
Haoqi Li, Ming Tu, Jing Huang +2
Representation learning for speech emotion recognition is challenging due to labeled data sparsity issue and lack of gold standard references. In addition, there is much variabilit…
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…
Improving Graph Attention Networks with Large Margin-based Constraints
Guangtao Wang, Rex Ying, Jing Huang +1
Graph Attention Networks (GATs) are the state-of-the-art neural architecture for representation learning with graphs. GATs learn attention functions that assign weights to nodes so…
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…
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…
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…
I4U Submission to NIST SRE 2018: Leveraging from a Decade of Shared Experiences
Kong Aik Lee, Ville Hautamaki, Tomi Kinnunen +43
The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which…
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…