querysum | EMNLP 20 : Coarse-to-Fine Query Focused Multi | Natural Language Processing library

querysum is a Python library typically used in Artificial Intelligence, Natural Language Processing, Pytorch, Bert applications. querysum has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This repository releases the code for Coarse-to-Fine Query Focused Multi-Document Summarization. Please cite the following paper [bib] if you use this code,. Xu, Yumo, and Mirella Lapata. "Coarse-to-Fine Query Focused Multi-Document Summarization." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 3632-3645. 2020. We consider the problem of better modeling query-cluster interactions to facilitate query focused multi-document summarization. Due to the lack of training data, existing work relies heavily on retrieval-style methods for assembling query relevant summaries. We propose a coarse-to-fine modeling framework which employs progressively more accurate modules for estimating whether text segments are relevant, likely to contain an answer, and central. The modules can be independently developed and leverage training data if available. We present an instantiation of this framework with a trained evidence estimator which relies on distant supervision from question answering (where various resources exist) to identify segments which are likely to answer the query and should be included in the summary. Our framework is robust across domains and query types (i.e., long vs short) and outperforms strong comparison systems on benchmark datasets. Should you have any query please contact me at yumo.xu@ed.ac.uk.