Adversarial NLI for Factual Correctness in Text Summarisation Models

24 May 2020

Papers citing "Adversarial NLI for Factual Correctness in Text Summarisation Models"

7 / 7 papers shown

Title
A Critical Evaluation of Evaluations for Long-form Question Answering Fangyuan Xu Yixiao Song Mohit Iyyer Eunsol Choi ELM 37 97 0 29 May 2023
Just ClozE! A Novel Framework for Evaluating the Factual Consistency Faster in Abstractive Summarization Yiyang Li Lei Li Marina Litvak N. Vanetik Dingxing Hu Yuze Li Yanquan Zhou HILM 40 0 0 06 Oct 2022
Don't Say What You Don't Know: Improving the Consistency of Abstractive Summarization by Constraining Beam Search Daniel King Zejiang Shen Nishant Subramani Daniel S. Weld Iz Beltagy Doug Downey HILM 28 31 0 16 Mar 2022
Investigating Crowdsourcing Protocols for Evaluating the Factual Consistency of Summaries Xiangru Tang Alexander R. Fabbri Haoran Li Ziming Mao Griffin Adams Borui Wang Asli Celikyilmaz Yashar Mehdad Dragomir R. Radev HILM 13 19 0 19 Sep 2021
Text Summarization with Pretrained Encoders Yang Liu Mirella Lapata MILM 258 1,433 0 22 Aug 2019
Hypothesis Only Baselines in Natural Language Inference Adam Poliak Jason Naradowsky Aparajita Haldar Rachel Rudinger Benjamin Van Durme 190 576 0 02 May 2018
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,690 0 28 Feb 2017