CO2Sum:Contrastive Learning for Factual-Consistent Abstractive
Summarization

CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization

2 December 2021

Wei Liu

Papers citing "CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization"

6 / 6 papers shown

Title
Factual Dialogue Summarization via Learning from Large Language Models Rongxin Zhu Jey Han Lau Jianzhong Qi HILM 46 1 0 20 Jun 2024
Counterfactual Debiasing for Generating Factually Consistent Text Summaries Chenhe Dong Yuexiang Xie Yaliang Li Ying Shen CML HILM 22 0 0 18 May 2023
Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation Wenhao Wu Wei Li Jiachen Liu Xinyan Xiao Sujian Li Yajuan Lyu 24 3 0 22 Oct 2022
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
Factual Error Correction for Abstractive Summarization Models Mengyao Cao Yue Dong Jiapeng Wu Jackie C.K. Cheung HILM KELM 167 159 0 17 Oct 2020
SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents Ramesh Nallapati Feifei Zhai Bowen Zhou 207 1,253 0 14 Nov 2016