{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:53:04Z","timestamp":1763196784133,"version":"3.45.0"},"publisher-location":"Singapore","reference-count":28,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819533480","type":"print"},{"value":"9789819533497","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T00:00:00Z","timestamp":1763251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T00:00:00Z","timestamp":1763251200000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-3349-7_5","type":"book-chapter","created":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:49:47Z","timestamp":1763196587000},"page":"55-67","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-task Contrastive Learning Enhanced Instruction Tuning for\u00a0Dialog Understanding"],"prefix":"10.1007","author":[{"given":"Zimeng","family":"Bai","sequence":"first","affiliation":[]},{"given":"Xiying","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Zhuoxin","family":"Han","sequence":"additional","affiliation":[]},{"given":"Haochen","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Lujie","family":"Niu","sequence":"additional","affiliation":[]},{"given":"Caixia","family":"Yuan","sequence":"additional","affiliation":[]},{"given":"Xiaojie","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,16]]},"reference":[{"key":"5_CR1","unstructured":"Achiam, J., Adler, S., Agarwal, S., et\u00a0al.: GPT-4 technical report. arXiv preprint arXiv:2303.08774 (2023)"},{"key":"5_CR2","unstructured":"Chen, G., Yao, Y., Wong, D.F., et\u00a0al.: A two-stage prediction-aware contrastive learning framework for multi-intent NLU. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pp. 1778\u20131788. ELRA and ICCL (2024)"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Cheng, X., Zhu, Z., Li, H., et\u00a0al.: Towards multi-intent spoken language understanding via hierarchical attention and optimal transport. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a038, pp. 17844\u201317852 (2024)","DOI":"10.1609\/aaai.v38i16.29738"},{"issue":"70","key":"5_CR4","first-page":"1","volume":"25","author":"HW Chung","year":"2024","unstructured":"Chung, H.W., Hou, L., Longpre, S., et al.: Scaling instruction-finetuned language models. J. Mach. Learn. Res. 25(70), 1\u201353 (2024)","journal-title":"J. Mach. Learn. Res."},{"key":"5_CR5","unstructured":"Coucke, A., Saade, A., Ball, A., et\u00a0al.: Snips voice platform: an embedded spoken language understanding system for private-by-design voice interfaces (2018)"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Gangadharaiah, R., Narayanaswamy, B.: Joint multiple intent detection and slot labeling for goal-oriented dialog. In: North American Chapter of the Association for Computational Linguistics, pp. 564\u2013569 (2019)","DOI":"10.18653\/v1\/N19-1055"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Goo, C.W., Gao, G., Hsu, Y.K., et\u00a0al.: Slot-gated modeling for joint slot filling and intent prediction. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pp. 753\u2013757. Association for Computational Linguistics (2018)","DOI":"10.18653\/v1\/N18-2118"},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Hemphill, C.T., Godfrey, J.J., Doddington, G.R.: The ATIS spoken language systems pilot corpus. In: Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, 24\u201327 June 1990 (1990)","DOI":"10.3115\/116580.116613"},{"key":"5_CR9","unstructured":"Hendrycks, D., Burns, C., Basart, S., et\u00a0al.: Measuring massive multitask language understanding. In: Proceedings of the International Conference on Learning Representations (ICLR) (2021)"},{"key":"5_CR10","unstructured":"Hu, J.E., Shen, Y., Wallis, P., et\u00a0al.: LoRa: low-rank adaptation of large language models. In: Proceedings of the International Conference on Learning Representations (ICLR) (2022)"},{"key":"5_CR11","doi-asserted-by":"publisher","first-page":"2123","DOI":"10.1109\/LSP.2022.3211156","volume":"29","author":"H Huang","year":"2022","unstructured":"Huang, H., Huang, P., Zhu, Z., et al.: CLID: a chunk-level intent detection framework for multiple intent spoken language understanding. IEEE Signal Process. Lett. 29, 2123\u20132127 (2022)","journal-title":"IEEE Signal Process. Lett."},{"key":"5_CR12","unstructured":"Liu, Y., Ott, M., Goyal, et\u00a0al.: RoBERTa: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)"},{"key":"5_CR13","unstructured":"Mirza, P., Sudhi, V., Sahoo, S.R., Bhat, S.R.: ILLUMINER: instruction-tuned large language models as few-shot intent classifier and slot filler. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pp. 8639\u20138651. ELRA and ICCL (2024)"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Pham, T., Tran, C., Nguyen, D.Q.: MISCA: a joint model for multiple intent detection and slot filling with intent-slot co-attention. In: Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 12641\u201312650. Association for Computational Linguistics (2023)","DOI":"10.18653\/v1\/2023.findings-emnlp.841"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Qin, L., Liu, T., Che, W., et\u00a0al.: A co-interactive transformer for joint slot filling and intent detection. In: ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8193\u20138197. IEEE (2021)","DOI":"10.1109\/ICASSP39728.2021.9414110"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Qin, L., Wei, F., Chen, Q., et\u00a0al.: CroPrompt: cross-task interactive prompting for zero-shot spoken language understanding. In: ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.\u00a01\u20135 (2025)","DOI":"10.1109\/ICASSP49660.2025.10889329"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Qin, L., Wei, F., Xie, T., et\u00a0al.: GL-GIN: fast and accurate non-autoregressive model for joint multiple intent detection and slot filling. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 178\u2013188. Association for Computational Linguistics (2021)","DOI":"10.18653\/v1\/2021.acl-long.15"},{"key":"5_CR18","doi-asserted-by":"crossref","unstructured":"Qin, L., Xu, X., Che, W., Liu, T.: AGIF: an adaptive graph-interactive framework for joint multiple intent detection and slot filling. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 1807\u20131816. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.findings-emnlp.163"},{"key":"5_CR19","unstructured":"Raffel, C., Shazeer, N.M., Roberts, A., et\u00a0al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21, 140:1\u2013140:67 (2019)"},{"key":"5_CR20","unstructured":"Touvron, H., Martin, L., Stone, K., et\u00a0al.: Llama 2: open foundation and fine-tuned chat models (2023)"},{"key":"5_CR21","first-page":"24824","volume":"35","author":"J Wei","year":"2022","unstructured":"Wei, J., Wang, X., Schuurmans, D., et al.: Chain-of-thought prompting elicits reasoning in large language models. Adv. Neural. Inf. Process. Syst. 35, 24824\u201324837 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"5_CR22","unstructured":"Wu, Y., Wang, H., Zhang, D., et\u00a0al.: Incorporating instructional prompts into a unified generative framework for joint multiple intent detection and slot filling. In: Proceedings of the 29th International Conference on Computational Linguistics, pp. 7203\u20137208. International Committee on Computational Linguistics (2022)"},{"key":"5_CR23","doi-asserted-by":"crossref","unstructured":"Xing, B., Liao, L., Huang, M., Tsang, I.: DC-instruct: an effective framework for generative multi-intent spoken language understanding. In: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 14520\u201314534. Association for Computational Linguistics (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.804"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"Xing, B., Tsang, I.W.H.: Co-guiding Net: achieving mutual guidances between multiple intent detection and slot filling via heterogeneous semantics-label graphs. In: Conference on Empirical Methods in Natural Language Processing, pp. 159\u2013169. Association for Computational Linguistics (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.12"},{"key":"5_CR25","doi-asserted-by":"crossref","unstructured":"Xu, P., Sarikaya, R.: Convolutional neural network based triangular CRF for joint intent detection and slot filling. In: 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, pp. 78\u201383. IEEE (2013)","DOI":"10.1109\/ASRU.2013.6707709"},{"key":"5_CR26","doi-asserted-by":"crossref","unstructured":"Yin, S., Huang, P., Xu, Y.: Uni-MIS: united multiple intent spoken language understanding via multi-view intent-slot interaction. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, pp. 19395\u201319403 (2024)","DOI":"10.1609\/aaai.v38i17.29910"},{"key":"5_CR27","unstructured":"Zhang, J., Gao, H., Zhang, P., et\u00a0al.: LA-UCL: LLM-augmented unsupervised contrastive learning framework for few-shot text classification. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pp. 10198\u201310207. ELRA and ICCL (2024)"},{"key":"5_CR28","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Xu, W., Cheng, X., et\u00a0al.: A dynamic graph interactive framework with label-semantic injection for spoken language understanding. In: ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.\u00a01\u20135. IEEE (2023)","DOI":"10.1109\/ICASSP49357.2023.10095809"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-3349-7_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T08:49:52Z","timestamp":1763196592000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-3349-7_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,16]]},"ISBN":["9789819533480","9789819533497"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-3349-7_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,16]]},"assertion":[{"value":"16 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Urumqi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2025\/index.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}