{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T04:47:01Z","timestamp":1785646021695,"version":"3.56.0"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032319326","type":"print"},{"value":"9783032319333","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-3-032-31933-3_13","type":"book-chapter","created":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T03:50:38Z","timestamp":1785642638000},"page":"185-197","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Self-supervised Learning of\u00a0Contextualized Neural Topic Models with\u00a0VIC Regularization"],"prefix":"10.1007","author":[{"given":"Kengo","family":"Hirami","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiran","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Koji","family":"Eguchi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"13_CR1","unstructured":"Bardes, A., Ponce, J., LeCun, Y.: VICReg: Variance-invariance-covariance regularization for self-supervised learning. In: International Conference on Learning Representations (2022). https:\/\/openreview.net\/forum?id=xm6YD62D1Ub"},{"key":"13_CR2","doi-asserted-by":"publisher","unstructured":"Bianchi, F., Terragni, S., Hovy, D.: Pre-training is a hot topic: Contextualized document embeddings improve topic coherence. In: Zong, C., Xia, F., Li, W., Navigli, R. (eds.) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp. 759\u2013766. Association for Computational Linguistics, Online (2021). https:\/\/doi.org\/10.18653\/v1\/2021.acl-short.96, https:\/\/aclanthology.org\/2021.acl-short.96\/","DOI":"10.18653\/v1\/2021.acl-short.96"},{"key":"13_CR3","unstructured":"Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3(null), 993\u20131022 (2003). https:\/\/dl.acm.org\/doi\/10.5555\/944919.944937"},{"key":"13_CR4","doi-asserted-by":"publisher","unstructured":"Card, D., Tan, C., Smith, N.A.: Neural models for documents with metadata. In: Gurevych, I., Miyao, Y. (eds.) Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 2031\u20132040. Association for Computational Linguistics, Melbourne, Australia (2018). https:\/\/doi.org\/10.18653\/v1\/P18-1189, https:\/\/aclanthology.org\/P18-1189\/","DOI":"10.18653\/v1\/P18-1189"},{"key":"13_CR5","doi-asserted-by":"publisher","unstructured":"Caron, M., Misra, I., Mairal, J., Goyal, P., Bojanowski, P., Joulin, A.: Unsupervised learning of visual features by contrasting cluster assignments. In: Proceedings of the 34th International Conference on Neural Information Processing Systems. NIPS \u201920, Curran Associates Inc, Red Hook, NY, USA (2020). https:\/\/doi.org\/10.5555\/3495724.3496555","DOI":"10.5555\/3495724.3496555"},{"key":"13_CR6","unstructured":"Chang, J., Gerrish, S., Wang, C., Boyd-graber, J., Blei, D.: Reading tea leaves: How humans interpret topic models. In: Bengio, Y., Schuurmans, D., Lafferty, J., Williams, C., Culotta, A. (eds.) Advances in Neural Information Processing Systems. vol.\u00a022. Curran Associates, Inc. (2009). https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2009\/file\/f92586a25bb3145facd64ab20fd554ff-Paper.pdf"},{"key":"13_CR7","doi-asserted-by":"publisher","unstructured":"Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning, pp. 1597\u20131607. PMLR (2020). https:\/\/doi.org\/10.5555\/3524938.3525087","DOI":"10.5555\/3524938.3525087"},{"key":"13_CR8","unstructured":"Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. CoRR abs\/1810.04805 (2018). http:\/\/arxiv.org\/abs\/1810.04805"},{"key":"13_CR9","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1162\/tacl_a_00325","volume":"8","author":"AB Dieng","year":"2020","unstructured":"Dieng, A.B., Ruiz, F.J., Blei, D.M.: Topic modeling in embedding spaces. Trans. Assoc. Comput. Linguist. 8, 439\u2013453 (2020)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Henderson, M., et al.: A repository of conversational datasets. In: Proceedings of the Workshop on NLP for Conversational AI (2019). https:\/\/arxiv.org\/abs\/1904.06472, data available at github.com\/PolyAI-LDN\/conversational-datasets","DOI":"10.18653\/v1\/W19-4101"},{"key":"13_CR11","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. In: Bengio, Y., LeCun, Y. (eds.) 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14-16, 2014, Conference Track Proceedings (2014). http:\/\/arxiv.org\/abs\/1312.6114"},{"key":"13_CR12","doi-asserted-by":"publisher","unstructured":"Lang, K.: Newsweeder: Learning to filter netnews. In: Machine learning proceedings, pp. 331\u2013339. Elsevier (1995). https:\/\/doi.org\/10.5555\/3091622.3091662","DOI":"10.5555\/3091622.3091662"},{"key":"13_CR13","unstructured":"Lee, J., et al.: Gemini embedding: Generalizable embeddings from gemini (2025). https:\/\/arxiv.org\/abs\/2503.07891"},{"key":"13_CR14","unstructured":"Liu, Y., et al.: Roberta: A robustly optimized BERT pretraining approach. CoRR abs\/1907.11692 (2019). http:\/\/arxiv.org\/abs\/1907.11692"},{"key":"13_CR15","unstructured":"Maas, A.L., Daly, R.E., Pham, P.T., Huang, D., Ng, A.Y., Potts, C.: Learning word vectors for sentiment analysis. In: Lin, D., Matsumoto, Y., Mihalcea, R. (eds.) Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pp. 142\u2013150. Association for Computational Linguistics, Portland, Oregon, USA (2011). https:\/\/aclanthology.org\/P11-1015\/"},{"key":"13_CR16","unstructured":"Merity, S., Xiong, C., Bradbury, J., Socher, R.: Pointer sentinel mixture models. In: International Conference on Learning Representations (2017). https:\/\/openreview.net\/forum?id=Byj72udxe"},{"key":"13_CR17","doi-asserted-by":"publisher","unstructured":"Miao, Y., Grefenstette, E., Blunsom, P.: Discovering discrete latent topics with neural variational inference. In: International Conference on Machine Learning, pp. 2410\u20132419. PMLR (2017). https:\/\/doi.org\/10.5555\/3305890.3305930","DOI":"10.5555\/3305890.3305930"},{"key":"13_CR18","unstructured":"Newman, D., Lau, J.H., Grieser, K., Baldwin, T.: Automatic evaluation of topic coherence. In: Kaplan, R., Burstein, J., Harper, M., Penn, G. (eds.) Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 100\u2013108. Association for Computational Linguistics, Los Angeles, California (2010). https:\/\/aclanthology.org\/N10-1012\/"},{"key":"13_CR19","unstructured":"Nguyen, T., Luu, A.T.: Contrastive learning for neural topic model. Adv. Neural Inf. Process. Syst. 34, 11974\u201311986 (2021). https:\/\/openreview.net\/forum?id=NEgqO9yB7e"},{"key":"13_CR20","doi-asserted-by":"publisher","unstructured":"Reimers, N., Gurevych, I.: Sentence-BERT: Sentence embeddings using Siamese BERT-networks. In: Inui, K., Jiang, J., Ng, V., Wan, X. (eds.) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 3982\u20133992. Association for Computational Linguistics, Hong Kong, China (2019). https:\/\/doi.org\/10.18653\/v1\/D19-1410, https:\/\/aclanthology.org\/D19-1410\/","DOI":"10.18653\/v1\/D19-1410"},{"key":"13_CR21","doi-asserted-by":"publisher","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: Facenet: A unified embedding for face recognition and clustering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7298682","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"13_CR22","doi-asserted-by":"publisher","unstructured":"Song, K., Tan, X., Qin, T., Lu, J., Liu, T.Y.: Mpnet: masked and permuted pre-training for language understanding. In: Proceedings of the 34th International Conference on Neural Information Processing Systems. NIPS \u201920, Curran Associates Inc, Red Hook, NY, USA (2020). https:\/\/doi.org\/10.5555\/3495724.3497138","DOI":"10.5555\/3495724.3497138"},{"key":"13_CR23","unstructured":"Srivastava, A., Sutton, C.: Autoencoding variational inference for topic models. In: International Conference on Learning Representations (2017). https:\/\/openreview.net\/forum?id=BybtVK9lg"},{"key":"13_CR24","doi-asserted-by":"publisher","unstructured":"Touvron, H., et al.: Llama 2: Open foundation and fine-tuned chat models (2023). https:\/\/doi.org\/10.48550\/arXiv.2307.09288, https:\/\/www.semanticscholar.org\/paper\/104b0bb1da562d53cbda87aec79ef6a2827d191a","DOI":"10.48550\/arXiv.2307.09288"},{"key":"13_CR25","doi-asserted-by":"crossref","unstructured":"Xu, W., Hirami, K., Eguchi, K.: Self-supervised learning for neural topic models with variance-invariance-covariance regularization. Knowl. Inf. Syst. (2025)","DOI":"10.1007\/s10115-025-02367-9"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-31933-3_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T03:50:41Z","timestamp":1785642641000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-31933-3_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,3]]},"ISBN":["9783032319326","9783032319333"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-31933-3_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,3]]},"assertion":[{"value":"3 August 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lyon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 August 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2026.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}