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Can We Achieve More with Less? Exploring Data Augmentation for Toxic
  Comment Classification

Can We Achieve More with Less? Exploring Data Augmentation for Toxic Comment Classification

2 July 2020
Chetanya Rastogi
Nikka Mofid
Fang-I Hsiao
ArXivPDFHTML

Papers citing "Can We Achieve More with Less? Exploring Data Augmentation for Toxic Comment Classification"

3 / 3 papers shown
Title
Data Augmentation using Transformers and Similarity Measures for
  Improving Arabic Text Classification
Data Augmentation using Transformers and Similarity Measures for Improving Arabic Text Classification
Dania Refai
Saleh Abu-Soud
Mohammad J. Abdel-Rahman
40
12
0
28 Dec 2022
Data Augmentation Approaches in Natural Language Processing: A Survey
Data Augmentation Approaches in Natural Language Processing: A Survey
Bohan Li
Yutai Hou
Wanxiang Che
130
270
0
05 Oct 2021
Megatron-LM: Training Multi-Billion Parameter Language Models Using
  Model Parallelism
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
M. Shoeybi
M. Patwary
Raul Puri
P. LeGresley
Jared Casper
Bryan Catanzaro
MoE
245
1,821
0
17 Sep 2019
1