Extractive is not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization

8 September 2022

Papers citing "Extractive is not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization"

9 / 9 papers shown

Title
Context-Aware Hierarchical Merging for Long Document Summarization Litu Ou Mirella Lapata MoMe 96 1 0 03 Feb 2025
SEMQA: Semi-Extractive Multi-Source Question Answering Tal Schuster Á. Lelkes Haitian Sun Jai Gupta Jonathan Berant W. Cohen Donald Metzler 21 13 0 08 Nov 2023
STRONG -- Structure Controllable Legal Opinion Summary Generation Yang Zhong Diane Litman ELM AILaw 19 1 0 29 Sep 2023
What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization Griffin Adams Bichlien H. Nguyen Jake A. Smith Yingce Xia Shufang Xie Anna Ostropolets Budhaditya Deb Yuan Chen Tristan Naumann Noémie Elhadad 13 8 0 12 May 2023
Finding a Balanced Degree of Automation for Summary Evaluation Shiyue Zhang Mohit Bansal 47 43 0 23 Sep 2021
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics Artidoro Pagnoni Vidhisha Balachandran Yulia Tsvetkov HILM 215 305 0 27 Apr 2021
GO FIGURE: A Meta Evaluation of Factuality in Summarization Saadia Gabriel Asli Celikyilmaz Rahul Jha Yejin Choi Jianfeng Gao HILM 227 96 0 24 Oct 2020
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages Peng Qi Yuhao Zhang Yuhui Zhang Jason Bolton Christopher D. Manning AI4TS 184 1,638 0 16 Mar 2020
Teaching Machines to Read and Comprehend Karl Moritz Hermann Tomás Kociský Edward Grefenstette L. Espeholt W. Kay Mustafa Suleyman Phil Blunsom 170 3,504 0 10 Jun 2015