Towards Reliable and Factual Response Generation: Detecting Unanswerable Questions in Information-Seeking Conversations

Author:

Łajewska WeronikaORCID,Balog KrisztianORCID

Publisher

Springer Nature Switzerland

Reference24 articles.

1. Asai, A., Choi, E.: Challenges in information-seeking QA: unanswerable questions and paragraph retrieval. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing. ACL-IJNLP ’21, vol. 1, pp. 1492–1504 (2021)

2. Bolotova-Baranova, V., Blinov, V., Filippova, S., Scholer, F., Sanderson, M.: WikiHowQA: A comprehensive benchmark for multi-document non-factoid question answering. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics. ACL ’23 (2023)

3. Cao, Z., Li, W., Li, S., Wei, F., Li, Y.: AttSum: joint learning of focusing and summarization with neural attention. In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics. COLING ’16, pp. 547–556 (2016)

4. Choi, E., et al.: QuAC: question answering in context. In: Findings of the Association for Computational Linguistics: EMNLP 2018. EMNLP ’18, pp. 2174–2184 (2018)

5. Dalton, J., Xiong, C., Callan, J.: TREC CAsT 2019: the conversational assistance track overview. In: The Twenty-Eighth Text Retrieval Conference Proceedings. TREC ’19 (2019)

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