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2020.emnlp-main.741.pdf
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🔗 Source: aclanthology.org
📊 Size: 1.26 MB
👤 Author: Zibo Lin ; Deng Cai ; Yan Wang ; Xiaojiang Liu ; Haitao Zheng ; Shuming Shi
⬇️ Downloads: 78

Summary

Learning to Rank with Grayscale Data for Dialogue Response Selection. Researchers propose a method to automatically construct grayscale data for training dialogue response selection models, using off-the-shelf retrieval algorithms and generation models to create responses with varying levels of relevance. This approach allows for multi-level ranking objectives, which can improve the model's ability to capture fine-grained context-response relevance differences and reduce the train-test discrepancy in terms of distractor strength. Experiments on three benchmark datasets and four state-of-the-art matching models show significant and consistent performance improvements.

Description

Learning to Rank with Grayscale Data for Dialogue Response Selection.

Technical Information

  • File Format: PDF
  • File Size: 1.26 MB
  • Pages: 10
  • Language: EN
  • Author: Zibo Lin ; Deng Cai ; Yan Wang ; Xiaojiang Liu ; Haitao Zheng ; Shuming Shi
  • Total Downloads: 78
  • Last Updated: 4 hours ago

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