941 citations · 5.4k across the 87 of their papers we have counts for
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Can Monolingual Pretrained Models Help Cross-Lingual Classification?
Zewen Chi, Li Dong, Furu Wei +2
Multilingual pretrained language models (such as multilingual BERT) have achieved impressive results for cross-lingual transfer. However, due to the constant model capacity, multil…
Transforming Wikipedia into Augmented Data for Query-Focused Summarization
Haichao Zhu, Li Dong, Furu Wei +2
The limited size of existing query-focused summarization datasets renders training data-driven summarization models challenging. Meanwhile, the manual construction of a query-focus…
Cross-Lingual Natural Language Generation via Pre-Training
Zewen Chi, Li Dong, Furu Wei +3
In this work we focus on transferring supervision signals of natural language generation (NLG) tasks between multiple languages. We propose to pretrain the encoder and the decoder…
Visualizing and Understanding the Effectiveness of BERT
Yaru Hao, Li Dong, Furu Wei +1
Language model pre-training, such as BERT, has achieved remarkable results in many NLP tasks. However, it is unclear why the pre-training-then-fine-tuning paradigm can improve perf…
Learning to Ask Unanswerable Questions for Machine Reading Comprehension
Haichao Zhu, Li Dong, Furu Wei +3
Machine reading comprehension with unanswerable questions is a challenging task. In this work, we propose a data augmentation technique by automatically generating relevant unanswe…
Data-to-text Generation with Entity Modeling
Ratish Puduppully, Li Dong, Mirella Lapata
Recent approaches to data-to-text generation have shown great promise thanks to the use of large-scale datasets and the application of neural network architectures which are traine…