Le Hu

Sliding Selector Network with Dynamic Memory for Extractive Summarization of Long Documents

2021

Neural-based summarization models suffer from the length limitation of text encoder. Long documents have to been truncated before they are sent to the model, which results in huge loss of summary-relevant contents. To address this …

ListReader: Extracting List-form Answers for Opinion Questions

2021 · arXiv (Cornell University)

Question answering (QA) is a high-level ability of natural language processing. Most extractive ma-chine reading comprehension models focus on factoid questions (e.g., who, when, where) and restrict the output answer as a short and continuous …

Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks

2020

Text summarization aims to compress a textual document to a short summary while keeping salient information. Extractive approaches are widely used in text summarization because of their fluency and efficiency. However, most of existing extractive …