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2020.emnlp-main.413.pdf
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🔗 Source: aclanthology.org
📊 Size: 1.15 MB
👤 Author: Xilun Chen ; Asish Ghoshal ; Yashar Mehdad ; Luke Zettlemoyer ; Sonal Gupta
⬇️ Downloads: 71

Summary

Researchers propose a novel method for low-resource domain adaptation in task-oriented semantic parsing, outperforming supervised neural models with 10-fold less data. They identify two key factors: better representation learning using BART and better training techniques with optimization-based meta-learning. Experiments on a new multi-domain dataset (TOPv2) show significant improvements over baseline models in low-data regimes, achieving competitive performance with 10x less data.

Description

Researchers propose a novel method for low-resource domain adaptation in task-oriented semantic parsing, outperforming supervised neural models with 10-fold...

Technical Information

  • File Format: PDF
  • File Size: 1.15 MB
  • Pages: 11
  • Language: EN
  • Author: Xilun Chen ; Asish Ghoshal ; Yashar Mehdad ; Luke Zettlemoyer ; Sonal Gupta
  • Total Downloads: 71
  • Last Updated: 5 hours ago

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