{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T07:14:29Z","timestamp":1760426069494,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031084720"},{"type":"electronic","value":"9783031084737"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-08473-7_12","type":"book-chapter","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T18:03:10Z","timestamp":1655402590000},"page":"127-134","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Metric Learning and\u00a0Adaptive Boundary for\u00a0Out-of-Domain Detection"],"prefix":"10.1007","author":[{"given":"Petr","family":"Lorenc","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tommaso","family":"Gargiani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Pichl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jakub","family":"Konr\u00e1d","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Petr","family":"Marek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ond\u0159ej","family":"Kobza","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"\u0160ediv\u00fd","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,13]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Casanueva, I., Temcinas, T., Gerz, D., Henderson, M., Vulic, I.: Efficient Intent Detection with Dual Sentence Encoders. Association for Computational Linguistics (2020)","key":"12_CR1","DOI":"10.18653\/v1\/2020.nlp4convai-1.5"},{"unstructured":"Cer, D., et al.: Universal sentence encoder. arXiv preprint arXiv:1803.11175 (2018)","key":"12_CR2"},{"doi-asserted-by":"crossref","unstructured":"Chen, D., Yu, Z.: Gold: improving out-of-scope detection in dialogues using data augmentation. In: Empirical Methods in Natural Language Processing, pp. 402\u2013434 (2021)","key":"12_CR3","DOI":"10.18653\/v1\/2021.emnlp-main.35"},{"doi-asserted-by":"crossref","unstructured":"Chen, W., Chen, X., Zhang, J., Huang, K.: Beyond triplet loss: a deep quadruplet network for person re-identification. In: Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1320\u20131329 (2017)","key":"12_CR4","DOI":"10.1109\/CVPR.2017.145"},{"unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. In: North American Association for Computational Linguistics, pp. 68\u201394 (2019)","key":"12_CR5"},{"doi-asserted-by":"crossref","unstructured":"Finch, J.D., et al.: Emora: an inquisitive social chatbot who cares for you. In: Alexa Prize Processing, vol. 3 (2020)","key":"12_CR6","DOI":"10.2307\/j.ctv15wxnsd.6"},{"unstructured":"Hendrycks, D., Gimpel, K.: A baseline for detecting misclassified and out-of-distribution examples in neural networks (2016)","key":"12_CR7"},{"doi-asserted-by":"crossref","unstructured":"Hoffer, E., Ailon, N.: Deep metric learning using triplet network. In: Feragen, A., Pelillo, M., Loog, M. (eds.) Similarity-Based Pattern Recognition, pp. 84\u201392 (2015)","key":"12_CR8","DOI":"10.1007\/978-3-319-24261-3_7"},{"doi-asserted-by":"publisher","unstructured":"Keet, C.M.: Open World Assumption, pp. 1567\u20131567. Springer, New York (2013). https:\/\/doi.org\/10.1007\/978-1-4419-9863-7_734","key":"12_CR9","DOI":"10.1007\/978-1-4419-9863-7_734"},{"unstructured":"Konr\u00e1d, J., et al.: Alquist 4.0: towards social intelligence using generative models and dialogue personalization. In: Alexa Prize Proceeding, vol. 4 (2021)","key":"12_CR10"},{"doi-asserted-by":"crossref","unstructured":"Larson, S., et al.: An evaluation dataset for intent classification and out-of-scope prediction. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (2019)","key":"12_CR11","DOI":"10.18653\/v1\/D19-1131"},{"doi-asserted-by":"crossref","unstructured":"Lin, T.E., Xu, H.: Deep unknown intent detection with margin loss. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 5491\u20135496 (2019)","key":"12_CR12","DOI":"10.18653\/v1\/P19-1548"},{"doi-asserted-by":"publisher","unstructured":"Moore, R.J., Arar, R.: Conversational UX design: an introduction. In: Moore, R.J., Szymanski, M.H., Arar, R., Ren, G.-J. (eds.) Studies in Conversational UX Design. HIS, pp. 1\u201316. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-95579-7_1","key":"12_CR13","DOI":"10.1007\/978-3-319-95579-7_1"},{"unstructured":"Pichl, J., Marek, P., Konr\u00e1d, J., Lorenc, P., Ta, V.D., Sediv\u00fd, J.: Alquist 3.0: Alexa prize bot using conversational knowledge graph. In: Alexa Prize Processing, vol. 3 (2020)","key":"12_CR14"},{"doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-Bert: sentence embeddings using Siamese Bert-networks. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (2019)","key":"12_CR15","DOI":"10.18653\/v1\/D19-1410"},{"unstructured":"Shafaei, A., Schmidt, M., Little, J.J.: A less biased evaluation of out-of-distribution sample detectors. In: BMVC, p. 3 (2019)","key":"12_CR16"},{"doi-asserted-by":"crossref","unstructured":"Shu, L., Benajiba, Y., Mansour, S., Zhang, Y.: Odist: open world classification via distributionally shifted instances. In: Empirical Methods in Natural Language Processing (2021)","key":"12_CR17","DOI":"10.18653\/v1\/2021.findings-emnlp.316"},{"doi-asserted-by":"crossref","unstructured":"Shu, L., Xu, H., Liu, B.: Doc: deep open classification of text documents. In: Empirical Methods in Natural Language Processing, pp. 2911\u20132916 (2017)","key":"12_CR18","DOI":"10.18653\/v1\/D17-1314"},{"doi-asserted-by":"crossref","unstructured":"Sun, Y., et al.: Circle loss: a unified perspective of pair similarity optimization. In: Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6397\u20136406 (2020)","key":"12_CR19","DOI":"10.1109\/CVPR42600.2020.00643"},{"doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: Cosface: large margin cosine loss for deep face recognition. In: CVPR, pp. 5612\u20135634 (2018)","key":"12_CR20","DOI":"10.1109\/CVPR.2018.00552"},{"doi-asserted-by":"crossref","unstructured":"Zhang, H., Xu, H., Lin, T.E.: Deep open intent classification with adaptive decision boundary. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 14374\u201314382 (2021)","key":"12_CR21","DOI":"10.1609\/aaai.v35i16.17690"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-08473-7_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T08:43:21Z","timestamp":1700729001000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-08473-7_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031084720","9783031084737"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-08473-7_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"13 June 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLDB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications of Natural Language to Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Valencia","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nldb2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/nldb2022.prhlt.upv.es\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"106","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}