Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models

23 February 2024

Papers citing "Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models"

7 / 7 papers shown

Title
Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling Vidhisha Balachandran Hannaneh Hajishirzi William W. Cohen Yulia Tsvetkov HILM KELM 82 46 0 22 Oct 2022
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization Dheeraj Rajagopal Siamak Shakeri Cicero Nogueira dos Santos Eduard H. Hovy Chung-Ching Chang HILM 72 10 0 25 May 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 303 11,881 0 04 Mar 2022
Entity-Based Knowledge Conflicts in Question Answering Shayne Longpre Kartik Perisetla Anthony Chen Nikhil Ramesh Chris DuBois Sameer Singh HILM 241 236 0 10 Sep 2021
The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey Yi-Chong Huang Xiachong Feng Xiaocheng Feng Bing Qin HILM 128 104 0 30 Apr 2021
Entity-level Factual Consistency of Abstractive Text Summarization Feng Nan Ramesh Nallapati Zhiguo Wang Cicero Nogueira dos Santos Henghui Zhu Dejiao Zhang Kathleen McKeown Bing Xiang HILM 142 157 0 18 Feb 2021
Teaching Machines to Read and Comprehend Karl Moritz Hermann Tomás Kociský Edward Grefenstette L. Espeholt W. Kay Mustafa Suleyman Phil Blunsom 170 3,508 0 10 Jun 2015