559 citations · 2.2k across the 49 of their papers we have counts for
6 papers · 1 filter
Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base
Tao Shen, Xiubo Geng, Tao Qin +5
We consider the problem of conversational question answering over a large-scale knowledge base. To handle huge entity vocabulary of a large-scale knowledge base, recent neural sema…
Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning
Yibo Sun, Duyu Tang, Nan Duan +4
Neural semantic parsing has achieved impressive results in recent years, yet its success relies on the availability of large amounts of supervised data. Our goal is to learn a neur…
Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
Shangwen Lv, Daya Guo, Jingjing Xu +7
Commonsense question answering aims to answer questions which require background knowledge that is not explicitly expressed in the question. The key challenge is how to obtain evid…
Reasoning Over Semantic-Level Graph for Fact Checking
Wanjun Zhong, Jingjing Xu, Duyu Tang +5
Fact checking is a challenging task because verifying the truthfulness of a claim requires reasoning about multiple retrievable evidence. In this work, we present a method suitable…
Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing
Daya Guo, Duyu Tang, Nan Duan +2
In this paper, we present an approach to incorporate retrieved datapoints as supporting evidence for context-dependent semantic parsing, such as generating source code conditioned…
Deep Reason: A Strong Baseline for Real-World Visual Reasoning
Chenfei Wu, Yanzhao Zhou, Gen Li +3
This paper presents a strong baseline for real-world visual reasoning (GQA), which achieves 60.93% in GQA 2019 challenge and won the sixth place. GQA is a large dataset with 22M qu…