19 citations · 29 across the 4 of their papers we have counts for
8 papers
Accelerating Road Sign Ground Truth Construction with Knowledge Graph and Machine Learning
Ji Eun Kim, Cory Henson, Kevin Huang +2
Having a comprehensive, high-quality dataset of road sign annotation is critical to the success of AI-based Road Sign Recognition (RSR) systems. In practice, annotators often face…
Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling
Wenxuan Zhou, Kevin Huang, Tengyu Ma +1
Document-level relation extraction (RE) poses new challenges compared to its sentence-level counterpart. One document commonly contains multiple entity pairs, and one entity pair o…
Entity and Evidence Guided Relation Extraction for DocRED
Kevin Huang, Guangtao Wang, Tengyu Ma +1
Document-level relation extraction is a challenging task which requires reasoning over multiple sentences in order to predict relations in a document. In this paper, we pro-pose a…
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…