Can I Be of Further Assistance? Using Unstructured Knowledge Access to Improve Task-oriented Conversational Modeling

  title={Can I Be of Further Assistance? Using Unstructured Knowledge Access to Improve Task-oriented Conversational Modeling},
  author={Di Jin and S. Kim and Dilek Z. Hakkani-T{\"u}r},
Most prior work on task-oriented dialogue systems are restricted to limited coverage of domain APIs. However, users oftentimes have requests that are out of the scope of these APIs. This work focuses on responding to these beyond-API-coverage user turns by incorporating external, unstructured knowledge sources. Our approach works in a pipelined manner with knowledge-seeking turn detection, knowledge selection, and response generation in sequence. We introduce novel data augmentation methods for… Expand


Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access
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Learning Fine-Grained Image Similarity with Deep Ranking
  • Jiang Wang, Yang Song, +5 authors Y. Wu
  • Computer Science
  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • 2014
A deep ranking model that employs deep learning techniques to learn similarity metric directly from images has higher learning capability than models based on hand-crafted features and deep classification models. Expand