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Multilingual Pre-Trained Transformers and Convolutional NN Classification Models for Technical Domain Identification

arXiv 2101.09012 ↗First posted 22 Jan 2021cs.CLcited by 0

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Abstract (arXiv)

In this paper, we present a transfer learning system to perform technical domain identification on multilingual text data. We have submitted two runs, one uses the transformer model BERT, and the other uses XLM-ROBERTa with the CNN model for text classification. These models allowed us to identify the domain of the given sentences for the ICON 2020 shared Task, TechDOfication: Technical Domain Identification. Our system ranked the best for the subtasks 1d, 1g for the given TechDOfication dataset.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 9 references that are in the map. First posted on arXiv 22 Jan 2021.

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References · 6

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  4. 2014Convolutional Neural Networks for Sentence Classificationcited by 1,127
  5. 2018Graph Convolutional Networks for Text Classificationcited by 345
  6. 2019DocBERT: BERT for Document Classificationcited by 68

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