ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2104.08724
  4. Cited By
Extract, Denoise and Enforce: Evaluating and Improving Concept
  Preservation for Text-to-Text Generation

Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation

18 April 2021
Yuning Mao
Wenchang Ma
Deren Lei
Jiawei Han
Xiang Ren
ArXivPDFHTML

Papers citing "Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation"

3 / 3 papers shown
Title
Entity-level Factual Consistency of Abstractive Text Summarization
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
Constrained Abstractive Summarization: Preserving Factual Consistency
  with Constrained Generation
Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation
Yuning Mao
Xiang Ren
Heng Ji
Jiawei Han
HILM
115
38
0
24 Oct 2020
Text Summarization with Pretrained Encoders
Text Summarization with Pretrained Encoders
Yang Liu
Mirella Lapata
MILM
254
1,430
0
22 Aug 2019
1