1.5k citations · 2.9k across the 32 of their papers we have counts for
12 papers · 1 filter
Improving Reinforcement Learning Based Image Captioning with Natural Language Prior
Tszhang Guo, Shiyu Chang, Mo Yu +1
Recently, Reinforcement Learning (RL) approaches have demonstrated advanced performance in image captioning by directly optimizing the metric used for testing. However, this shaped…
Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks
Linfeng Song, Zhiguo Wang, Mo Yu +3
Multi-hop reading comprehension focuses on one type of factoid question, where a system needs to properly integrate multiple pieces of evidence to correctly answer a question. Prev…
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain
Xiaoyan Wang, Pavan Kapanipathi, Ryan Musa +8
Natural Language Inference (NLI) is fundamental to many Natural Language Processing (NLP) applications including semantic search and question answering. The NLI problem has gained…
Deriving Machine Attention from Human Rationales
Yujia Bao, Shiyu Chang, Mo Yu +1
Attention-based models are successful when trained on large amounts of data. In this paper, we demonstrate that even in the low-resource scenario, attention can be learned effectiv…
One-Shot Relational Learning for Knowledge Graphs
Wenhan Xiong, Mo Yu, Shiyu Chang +2
Knowledge graphs (KGs) are the key components of various natural language processing applications. To further expand KGs' coverage, previous studies on knowledge graph completion u…
Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model
Kun Xu, Lingfei Wu, Zhiguo Wang +3
Existing neural semantic parsers mainly utilize a sequence encoder, i.e., a sequential LSTM, to extract word order features while neglecting other valuable syntactic information su…