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Faithful to the Original: Fact Aware Neural Abstractive Summarization
Ziqiang Cao, Furu Wei, Wenjie Li +1
Unlike extractive summarization, abstractive summarization has to fuse different parts of the source text, which inclines to create fake facts. Our preliminary study reveals nearly…
S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension
Chuanqi Tan, Furu Wei, Nan Yang +3
In this paper, we present a novel approach to machine reading comprehension for the MS-MARCO dataset. Unlike the SQuAD dataset that aims to answer a question with exact text spans…
Entity Linking for Queries by Searching Wikipedia Sentences
Chuanqi Tan, Furu Wei, Pengjie Ren +2
We present a simple yet effective approach for linking entities in queries. The key idea is to search sentences similar to a query from Wikipedia articles and directly use the huma…
Selective Encoding for Abstractive Sentence Summarization
Qingyu Zhou, Nan Yang, Furu Wei +1
We propose a selective encoding model to extend the sequence-to-sequence framework for abstractive sentence summarization. It consists of a sentence encoder, a selective gate netwo…
Neural Question Generation from Text: A Preliminary Study
Qingyu Zhou, Nan Yang, Furu Wei +3
Automatic question generation aims to generate questions from a text passage where the generated questions can be answered by certain sub-spans of the given passage. Traditional me…