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Papers

Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access Track in DSTC9

2021-01-22 · Seokhwan Kim, Mihail Eric, Behnam Hedayatnia, Karthik Gopalakrishnan, Yang Liu, Chao-Wei Huang, Dilek Hakkani-Tur

Most prior work on task-oriented dialogue systems are restricted to a limited coverage of domain APIs, while users oftentimes have domain related requests that are not covered by the APIs. This challenge track aims to expand the coverage of task-oriented dialogue systems by incorporating external unstructured knowledge sources. We define three tasks: knowledge-seeking turn detection, knowledge selection, and knowledge-grounded response generation. We introduce the data sets and the neural baseline models for three tasks. The challenge track received a total of 105 entries from 24 participating teams. In the evaluation results, the ensemble methods with different large-scale pretrained language models achieved high performances with improved knowledge selection capability and better generalization into unseen data.

📄 PDF Abstract BibTeX arXiv:2101.09276

Code (1)

alexa/alexa-with-dstc9-track1-dataset 공식 구현 pytorch

Tasks

Response GenerationTask-Oriented Dialogue Systems

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