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Correcting Diverse Factual Errors in Abstractive Summarization via
  Post-Editing and Language Model Infilling

Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling

22 October 2022
Vidhisha Balachandran
Hannaneh Hajishirzi
William W. Cohen
Yulia Tsvetkov
    HILM
    KELM
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Papers citing "Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling"

10 / 10 papers shown
Title
Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generation
Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generation
Sha Li
Naren Ramakrishnan
RALM
KELM
145
1
0
18 Feb 2025
Factual Dialogue Summarization via Learning from Large Language Models
Factual Dialogue Summarization via Learning from Large Language Models
Rongxin Zhu
Jey Han Lau
Jianzhong Qi
HILM
28
1
0
20 Jun 2024
A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods
A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods
Hanlei Jin
Yang Zhang
Dan Meng
Jun Wang
Jinghua Tan
51
76
0
05 Mar 2024
KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large
  Language Models
KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Models
Yuyang Bai
Shangbin Feng
Vidhisha Balachandran
Zhaoxuan Tan
Shiqi Lou
Tianxing He
Yulia Tsvetkov
ELM
25
2
0
15 Oct 2023
Counterfactual Data Augmentation improves Factuality of Abstractive
  Summarization
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization
Dheeraj Rajagopal
Siamak Shakeri
Cicero Nogueira dos Santos
Eduard H. Hovy
Chung-Ching Chang
HILM
61
8
0
25 May 2022
The Factual Inconsistency Problem in Abstractive Text Summarization: A
  Survey
The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey
Yi-Chong Huang
Xiachong Feng
Xiaocheng Feng
Bing Qin
HILM
115
90
0
30 Apr 2021
Understanding Factuality in Abstractive Summarization with FRANK: A
  Benchmark for Factuality Metrics
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics
Artidoro Pagnoni
Vidhisha Balachandran
Yulia Tsvetkov
HILM
213
305
0
27 Apr 2021
Factual Error Correction for Abstractive Summarization Models
Factual Error Correction for Abstractive Summarization Models
Mengyao Cao
Yue Dong
Jiapeng Wu
Jackie C.K. Cheung
HILM
KELM
167
139
0
17 Oct 2020
Text Summarization with Pretrained Encoders
Text Summarization with Pretrained Encoders
Yang Liu
Mirella Lapata
MILM
245
1,417
0
22 Aug 2019
Teaching Machines to Read and Comprehend
Teaching Machines to Read and Comprehend
Karl Moritz Hermann
Tomás Kociský
Edward Grefenstette
L. Espeholt
W. Kay
Mustafa Suleyman
Phil Blunsom
167
3,504
0
10 Jun 2015
1