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Large language models as zero-shot dialogue state tracker through function calling. arXiv:2402.10466. 2024.","DOI":"10.18653\/v1\/2024.acl-long.471"},{"key":"ref15","doi-asserted-by":"crossref","unstructured":"Niu C, Wang X, Cheng X, Song J, Zhang T. 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Parameter-efficient low-resource dialogue state tracking by prompt tuning. arXiv:2301.10915. 2023.","DOI":"10.21437\/Interspeech.2023-2238"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"8347","DOI":"10.1007\/s10489-024-05571-2","article-title":"UTMGAT: a unified transformer with memory encoder and graph attention networks for multidomain dialogue state tracking","volume":"54","author":"Khan","year":"2024","journal-title":"Appl Intell"},{"key":"ref20","unstructured":"Saha D, Santra B, Goyal P. A study on prompt-based few-shot learning methods for belief state tracking in task-oriented dialog systems. arXiv:2204.08167. 2022."},{"key":"ref21","series-title":"Proceedings of the ACM Web Conference; 2023 Apr 30","first-page":"1468","article-title":"A Dual prompt learning framework for few-shot dialogue state tracking","author":"Yang","year":"2023"},{"key":"ref22","series-title":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers); 2022 May 22\u201327","first-page":"1124","article-title":"Continual prompt tuning for dialog state tracking","author":"Zhu"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"111542","DOI":"10.1016\/j.knosys.2024.111542","article-title":"DSTEA: improving dialogue state tracking via entity adaptive pre-training","volume":"290","author":"Lee","year":"2024","journal-title":"Knowl Based Syst"},{"key":"ref24","series-title":"Proceedings of the Web Conference; 2021 Apr 19\u201323","first-page":"1598","article-title":"Slot self-attentive dialogue state tracking","author":"Ye"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.3390\/app13031775","article-title":"A multi-attention approach using BERT and stacked bidirectional LSTM for improved dialogue state tracking","volume":"13","author":"Khan","year":"2023","journal-title":"Appl Sci"},{"key":"ref26","series-title":"Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)","first-page":"310","article-title":"Extrinsic evaluation of dialog state tracking and predictive metrics for dialog policy optimization","author":"Lee","year":"2014"},{"key":"ref27","series-title":"Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)","first-page":"318","article-title":"The SJTU system for dialog state tracking challenge 2","author":"Sun","year":"2014"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"1160","DOI":"10.1109\/JPROC.2012.2225812","article-title":"POMDP-based statistical spoken dialog systems: a review","volume":"101","author":"Young","year":"2013","journal-title":"Proc IEEE"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1016\/j.csl.2009.07.003","article-title":"Bayesian update of dialogue state: a POMDP framework for spoken dialogue systems","volume":"24","author":"Thomson","year":"2010","journal-title":"Comput Speech Lang"},{"key":"ref30","series-title":"Proceedings of the SIGDIAL 2013 Conference; 2013 Aug 22\u201324","first-page":"457","article-title":"Dialog state tracking using conditional random fields","author":"Ren","year":"2013"},{"key":"ref31","unstructured":"Noroozi V, Zhang Y, Bakhturina E, Kornuta T. A fast and robust BERT-based dialogue state tracker for schema-guided dialogue dataset. arXiv:2008.12335. 2020."},{"key":"ref32","doi-asserted-by":"crossref","first-page":"101460","DOI":"10.1016\/j.csl.2022.101460","article-title":"Knowledge-grounded dialogue modelling with dialogue-state tracking, domain tracking, and entity extraction","volume":"78","author":"Hong","year":"2023","journal-title":"Comput Speech Lang"},{"key":"ref33","first-page":"2627","author":"Hu","year":"2022","journal-title":"Findings of the Association for Computational"},{"key":"ref34","first-page":"8107","article-title":"MA-DST: multi-attention-based scalable dialog state tracking","volume":"34","author":"Kumar","year":"2020","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref35","unstructured":"Mou X, Sigouin B, Steenstra I, Su H. Multimodal dialogue state tracking by QA approach with data augmentation. arXiv:2007.09903. 2020."},{"key":"ref36","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1109\/TPAMI.2024.3463753","article-title":"T2TD: text-3D generation model based on prior knowledge guidance","volume":"47","author":"Nie","year":"2025","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref37","doi-asserted-by":"crossref","first-page":"111427","DOI":"10.1016\/j.engappai.2025.111427","article-title":"Can foundation language models predict fluid dynamics?","volume":"144","author":"Wang","year":"2025","journal-title":"Eng Appl Artif Intell"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"4277","DOI":"10.1007\/s11263-025-02392-9","article-title":"Fg-T2M++: LLMs-augmented fine-grained text driven human motion generation","volume":"133","author":"Wang","year":"2025","journal-title":"Int J Comput Vis"},{"key":"ref39","doi-asserted-by":"crossref","first-page":"110709","DOI":"10.1016\/j.patcog.2024.110709","article-title":"Cross-lingual font style transfer with full-domain convolutional attention","volume":"155","author":"Zhao","year":"2024","journal-title":"Pattern Recognit"},{"key":"ref40","unstructured":"Velickovic P, Cucurull G, Casanova A, Romero A, Lio P, Bengio Y, et al. Graph attention networks. arXiv:1710.10903. 2017."},{"key":"ref41","series-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing","first-page":"7871","article-title":"Knowledge-aware graph-enhanced GPT-2 for dialogue state tracking","author":"Lin","year":"2021"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.patrec.2023.03.024","article-title":"Enriching the dialogue state tracking model with a asyntactic discourse graph","volume":"169","author":"Yu","year":"2023","journal-title":"Patt Recognit Lett"},{"key":"ref43","series-title":"Findings of the Association for Computational Linguistics: EMNLP 2020","first-page":"766","article-title":"Efficient context and schema fusion networks for multi-domain dialogue state tracking","author":"Zhu","year":"2020"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"110069","DOI":"10.1016\/j.knosys.2022.110069","article-title":"Multi-task learning with graph attention networks for multi-domain task-oriented dialogue systems","volume":"259","author":"Zhao","year":"2023","journal-title":"Knowl Based Syst"},{"key":"ref45","doi-asserted-by":"crossref","first-page":"4829","DOI":"10.1007\/s00521-023-09328-9","article-title":"MGCRL: multi-view graph convolution and multi-agent reinforcement learning for dialogue state tracking","volume":"36","author":"Huang","year":"2024","journal-title":"Neural Comput Appl"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"109","DOI":"10.18653\/v1\/2020.nlp4convai-1.13","author":"Zang","year":"2020","journal-title":"Proceedings of the 2nd Workshop on Natural Language Processing for Conversational AI"},{"key":"ref47","unstructured":"Rastogi A, Zang X, Sunkara S, Gupta R, Khaitan P. Schema-guided dialogue state tracking task at DSTC8. arXiv:2002.01359. 2020."},{"key":"ref48","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI Blog"},{"key":"ref49","doi-asserted-by":"crossref","first-page":"5571","DOI":"10.1109\/TMC.2023.3314837","article-title":"Accuth+: accelerometer-based anti-spoofing voice authentication on wrist-worn wearables","volume":"23","author":"Han","year":"2023","journal-title":"IEEE Transact Mobile Comput"},{"key":"ref50","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1007\/s10489-025-06313-8","article-title":"Fpa-GCN: enhancing aspect sentiment triplet extraction with feature-rich prediction-aware graph convolutional networks","volume":"55","author":"Jiang","year":"2025","journal-title":"Appl Intell"},{"key":"ref51","series-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing","first-page":"5016","article-title":"MultiWOZ\u2014a large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling","author":"Budzianowski","year":"2018"},{"key":"ref52","series-title":"Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue","first-page":"351","article-title":"MultiWOZ 2.4: a multi-domain task-oriented dialogue dataset with essential annotation corrections to improve state tracking evaluation","author":"Ye","year":"2022"},{"journal-title":"3rd International Conference on Learning Representations, ICLR","year":"2015 May 7\u20139","author":"Kingma","key":"ref53"},{"key":"ref54","doi-asserted-by":"crossref","first-page":"420","DOI":"10.3390\/systems12100420","article-title":"Dynamic multi-granularity translation system: dag-structured multi-granularity representation and self-attention","volume":"12","author":"Lv","year":"2024","journal-title":"Systems"},{"key":"ref55","doi-asserted-by":"crossref","first-page":"109727","DOI":"10.1016\/j.ymssp.2022.109727","article-title":"Dual-microphone active noise cancellation paved with Doppler assimilation for TADS","volume":"184","author":"Liu","year":"2023","journal-title":"Mech Syst Signal Process"},{"key":"ref56","doi-asserted-by":"crossref","first-page":"111447","DOI":"10.1016\/j.patcog.2025.111447","article-title":"AttriDiffuser: adversarially enhanced diffusion model for text-to-facial attribute image synthesis","volume":"163","author":"Song","year":"2025","journal-title":"Pattern Recognit"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-85-3\/TSP_CMC_69134\/TSP_CMC_69134.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T02:23:54Z","timestamp":1763346234000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v85n3\/64190"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":56,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.069134","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2025-06-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-29","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-23","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}