Improving and Understanding Clarifying Question Generation in Conversational Search

Author:

Ortega Daniel,Söhnel Steven,Vu Ngoc Thang

Publisher

Springer Nature Switzerland

Reference31 articles.

1. IFIP Advances in Information and Communication Technology;E Adamopoulou,2020

2. Aliannejadi, M., Kiseleva, J., Chuklin, A., Dalton, J., Burtsev, M.: ConvAI3: generating clarifying questions for open-domain dialogue systems (ClariQ) (2020)

3. Aliannejadi, M., Kiseleva, J., Chuklin, A., Dalton, J., Burtsev, M.: Building and evaluating open-domain dialogue corpora with clarifying questions. In: Proceedings of the 2021 Conference on EMNLP. ACL, Dominican Republic (2021)

4. Banerjee, S., Lavie, A.: METEOR: an automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization. ACL, USA (2005)

5. Lecture Notes in Computer Science;J Bevendorff,2018

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