709 citations · 2.5k across the 39 of their papers we have counts for
13 papers · 1 filter
Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge
Kai Sun, Dian Yu, Jianshu Chen +2
In this paper, we aim to extract commonsense knowledge to improve machine reading comprehension. We propose to represent relations implicitly by situating structured knowledge in a…
Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension
Hongyu Gong, Yelong Shen, Dian Yu +2
In this paper, we study machine reading comprehension (MRC) on long texts, where a model takes as inputs a lengthy document and a question and then extracts a text span from the do…
Logical Natural Language Generation from Open-Domain Tables
Wenhu Chen, Jianshu Chen, Yu Su +2
Neural natural language generation (NLG) models have recently shown remarkable progress in fluency and coherence. However, existing studies on neural NLG are primarily focused on s…
Improving Pre-Trained Multilingual Models with Vocabulary Expansion
Hai Wang, Dian Yu, Kai Sun +2
Recently, pre-trained language models have achieved remarkable success in a broad range of natural language processing tasks. However, in multilingual setting, it is extremely reso…
TabFact: A Large-scale Dataset for Table-based Fact Verification
Wenhu Chen, Hongmin Wang, Jianshu Chen +5
The problem of verifying whether a textual hypothesis holds based on the given evidence, also known as fact verification, plays an important role in the study of natural language u…
Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention
Wenhu Chen, Jianshu Chen, Pengda Qin +2
Semantically controlled neural response generation on limited-domain has achieved great performance. However, moving towards multi-domain large-scale scenarios are shown to be diff…
Evidence Sentence Extraction for Machine Reading Comprehension
Hai Wang, Dian Yu, Kai Sun +4
Remarkable success has been achieved in the last few years on some limited machine reading comprehension (MRC) tasks. However, it is still difficult to interpret the predictions of…
DREAM: A Challenge Dataset and Models for Dialogue-Based Reading Comprehension
Kai Sun, Dian Yu, Jianshu Chen +3
We present DREAM, the first dialogue-based multiple-choice reading comprehension dataset. Collected from English-as-a-foreign-language examinations designed by human experts to eva…
Incorporating Structured Commonsense Knowledge in Story Completion
Jiaao Chen, Jianshu Chen, Zhou Yu
The ability to select an appropriate story ending is the first step towards perfect narrative comprehension. Story ending prediction requires not only the explicit clues within the…
XL-NBT: A Cross-lingual Neural Belief Tracking Framework
Wenhu Chen, Jianshu Chen, Yu Su +4
Task-oriented dialog systems are becoming pervasive, and many companies heavily rely on them to complement human agents for customer service in call centers. With globalization, th…
Character-level Deep Conflation for Business Data Analytics
Zhe Gan, P. D. Singh, Ameet Joshi +4
Connecting different text attributes associated with the same entity (conflation) is important in business data analytics since it could help merge two different tables in a databa…
Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads
Ji He, Mari Ostendorf, Xiaodong He +4
We introduce an online popularity prediction and tracking task as a benchmark task for reinforcement learning with a combinatorial, natural language action space. A specified numbe…
Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval
Hamid Palangi, Li Deng, Yelong Shen +5
This paper develops a model that addresses sentence embedding, a hot topic in current natural language processing research, using recurrent neural networks with Long Short-Term Mem…