709 citations · 2.5k across the 39 of their papers we have counts for
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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…
Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach
Shiyang Li, Jianshu Chen, Dian Yu
Recently, pretrained language models (e.g., BERT) have achieved great success on many downstream natural language understanding tasks and exhibit a certain level of commonsense rea…
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…
From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation
Yu Liu, Li Deng, Jianshu Chen +1
Many important classification problems, such as object classification, speech recognition, and machine translation, have been tackled by the supervised learning paradigm in the pas…
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…