22 citations · 48 across the 10 of their papers we have counts for
11 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…