1.9k citations · 10.4k across the 198 of their papers we have counts for
14 papers · 1 filter
Text Morphing
Shaohan Huang, Yu Wu, Furu Wei +1
In this paper, we introduce a novel natural language generation task, termed as text morphing, which targets at generating the intermediate sentences that are fluency and smooth wi…
Attention-Guided Answer Distillation for Machine Reading Comprehension
Minghao Hu, Yuxing Peng, Furu Wei +4
Despite that current reading comprehension systems have achieved significant advancements, their promising performances are often obtained at the cost of making an ensemble of nume…
Unsupervised Machine Commenting with Neural Variational Topic Model
Shuming Ma, Lei Cui, Furu Wei +1
Article comments can provide supplementary opinions and facts for readers, thereby increase the attraction and engagement of articles. Therefore, automatically commenting is helpfu…
Neural Melody Composition from Lyrics
Hangbo Bao, Shaohan Huang, Furu Wei +5
In this paper, we study a novel task that learns to compose music from natural language. Given the lyrics as input, we propose a melody composition model that generates lyrics-cond…
LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
Shuming Ma, Lei Cui, Damai Dai +2
We introduce the task of automatic live commenting. Live commenting, which is also called `video barrage', is an emerging feature on online video sites that allows real-time commen…
Neural Latent Extractive Document Summarization
Xingxing Zhang, Mirella Lapata, Furu Wei +1
Extractive summarization models require sentence-level labels, which are usually created heuristically (e.g., with rule-based methods) given that most summarization datasets only h…
Read + Verify: Machine Reading Comprehension with Unanswerable Questions
Minghao Hu, Furu Wei, Yuxing Peng +3
Machine reading comprehension with unanswerable questions aims to abstain from answering when no answer can be inferred. In addition to extract answers, previous works usually pred…
Reaching Human-level Performance in Automatic Grammatical Error Correction: An Empirical Study
Tao Ge, Furu Wei, Ming Zhou
Neural sequence-to-sequence (seq2seq) approaches have proven to be successful in grammatical error correction (GEC). Based on the seq2seq framework, we propose a novel fluency boos…
Neural Document Summarization by Jointly Learning to Score and Select Sentences
Qingyu Zhou, Nan Yang, Furu Wei +3
Sentence scoring and sentence selection are two main steps in extractive document summarization systems. However, previous works treat them as two separated subtasks. In this paper…
Sequential Copying Networks
Qingyu Zhou, Nan Yang, Furu Wei +1
Copying mechanism shows effectiveness in sequence-to-sequence based neural network models for text generation tasks, such as abstractive sentence summarization and question generat…
Dictionary-Guided Editing Networks for Paraphrase Generation
Shaohan Huang, Yu Wu, Furu Wei +1
An intuitive way for a human to write paraphrase sentences is to replace words or phrases in the original sentence with their corresponding synonyms and make necessary changes to e…
Response Generation by Context-aware Prototype Editing
Yu Wu, Furu Wei, Shaohan Huang +3
Open domain response generation has achieved remarkable progress in recent years, but sometimes yields short and uninformative responses. We propose a new paradigm for response gen…
Neural Open Information Extraction
Lei Cui, Furu Wei, Ming Zhou
Conventional Open Information Extraction (Open IE) systems are usually built on hand-crafted patterns from other NLP tools such as syntactic parsing, yet they face problems of erro…
Improv Chat: Second Response Generation for Chatbot
Furu Wei
Existing research on response generation for chatbot focuses on \textbf{First Response Generation} which aims to teach the chatbot to say the first response (e.g. a sentence) appro…