ConveRT for FAQ Answering
| Autor: | De Bruyn, Maxime, Lotfi, Ehsan, Buhmann, Jeska, Daelemans, Walter |
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| Rok vydání: | 2021 |
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| Druh dokumentu: | Working Paper |
| Popis: | Knowledgeable FAQ chatbots are a valuable resource to any organization. While powerful and efficient retrieval-based models exist for English, it is rarely the case for other languages for which the same amount of training data is not available. In this paper, we propose a novel pre-training procedure to adapt ConveRT, an English conversational retriever model, to other languages with less training data available. We apply it for the first time to the task of Dutch FAQ answering related to the COVID-19 vaccine. We show it performs better than an open-source alternative in both a low-data regime and a high-data regime. Comment: Accepted at bnaicbenelearn2021 |
| Databáze: | arXiv |
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