ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2011.01856
  4. Cited By
Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset
  Augmentation Using Graph Theory

Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory

3 November 2020
Hannah Chen
Yangfeng Ji
David Evans
ArXiv (abs)PDFHTML

Papers citing "Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory"

7 / 7 papers shown
Cyber-Attack Technique Classification Using Two-Stage Trained Large
  Language Models
Cyber-Attack Technique Classification Using Two-Stage Trained Large Language Models
Weiqiu You
Youngja Park
232
3
0
27 Nov 2024
Bridging the Gap between Decision and Logits in Decision-based Knowledge
  Distillation for Pre-trained Language Models
Bridging the Gap between Decision and Logits in Decision-based Knowledge Distillation for Pre-trained Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Qinhong Zhou
Zonghan Yang
Peng Li
Yang Liu
282
5
0
15 Jun 2023
GDA: Generative Data Augmentation Techniques for Relation Extraction
  Tasks
GDA: Generative Data Augmentation Techniques for Relation Extraction TasksAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Xuming Hu
Aiwei Liu
Zeqi Tan
Xin Zhang
Chenwei Zhang
Irwin King
Philip S. Yu
390
21
0
26 May 2023
Data Augmentation for Mental Health Classification on Social Media
Data Augmentation for Mental Health Classification on Social MediaICON (ICON), 2021
Gunjan Ansari
Muskan Garg
Chandni Saxena
210
24
0
19 Dec 2021
To Augment or Not to Augment? A Comparative Study on Text Augmentation
  Techniques for Low-Resource NLP
To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP
Gözde Gül Sahin
257
43
0
18 Nov 2021
Data Augmentation Methods for Anaphoric Zero Pronouns
Data Augmentation Methods for Anaphoric Zero Pronouns
Abdulrahman Aloraini
Massimo Poesio
243
5
0
20 Sep 2021
A Survey of Data Augmentation Approaches for NLP
A Survey of Data Augmentation Approaches for NLPFindings (Findings), 2021
Steven Y. Feng
Varun Gangal
Jason W. Wei
Sarath Chandar
Soroush Vosoughi
Teruko Mitamura
Eduard H. Hovy
AIMat
795
955
0
07 May 2021
1
Page 1 of 1