{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T08:03:52Z","timestamp":1784189032943,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819234165","type":"print"},{"value":"9789819234172","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T00:00:00Z","timestamp":1784246400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T00:00:00Z","timestamp":1784246400000},"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\/978-981-92-3417-2_40","type":"book-chapter","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T07:11:58Z","timestamp":1784185918000},"page":"470-481","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HUAB-RAG: Hierarchical Bandit-Based Adaptive Retrieval-Augmented Generation with Uncertainty Awareness"],"prefix":"10.1007","author":[{"given":"Li","family":"He","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guochen","family":"Hao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianyong","family":"Duan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,17]]},"reference":[{"key":"40_CR1","first-page":"9459","volume":"33","author":"P Lewis","year":"2020","unstructured":"Lewis, P., et al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. Adv. Neural Inf. Proces. Syst. 33, 9459\u20139474 (2020)","journal-title":"Adv. Neural Inf. Proces. Syst."},{"key":"40_CR2","unstructured":"Gao, Y. et al.: Retrieval-augmented generation for large language models: A survey. CoRR abs\/2312.10997 (2023)"},{"key":"40_CR3","first-page":"9802","volume-title":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics","author":"A Mallen","year":"2022","unstructured":"Mallen, A., Asai, A., Zhong, V., Das, R., Khashabi, D., Hajishirzi, H.: When not to trust language models: investigating effectiveness of parametric and non-parametric memories. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, pp. 9802\u20139822 (2022)"},{"key":"40_CR4","first-page":"1","volume-title":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics","author":"H Trivedi","year":"2022","unstructured":"Trivedi, H., Balasubramanian, N., Khot, T., Sabharwal, A.: Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, pp. 1\u201313 (2022)"},{"key":"40_CR5","first-page":"1","volume-title":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing","author":"Z Jiang","year":"2023","unstructured":"Jiang, Z., et al.: Active retrieval augmented generation. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 1\u201313 (2023)"},{"key":"40_CR6","first-page":"1","volume-title":"Proceedings of ICLR 2024","author":"A Asai","year":"2024","unstructured":"Asai, A., Wu, Z., Wang, Y., Sil, A., Hajishirzi, H.: Self-RAG: learning to retrieve, generate, and critique through self-reflection. In: Proceedings of ICLR 2024, pp. 1\u201313 (2024)"},{"key":"40_CR7","first-page":"7036","volume-title":"Proceedings of NAACL-HLT 2024","author":"S Jeong","year":"2024","unstructured":"Jeong, S., Baek, J., Cho, S., Hwang, S.J., Park, J.: Adaptive-RAG: learning to adapt retrieval-augmented large language models through question complexity. In: Proceedings of NAACL-HLT 2024, pp. 7036\u20137050 (2024)"},{"key":"40_CR8","first-page":"3248","volume-title":"Proceedings of COLING 2025","author":"X Tang","year":"2025","unstructured":"Tang, X., Gao, Q., Li, J., Du, N., Li, Q., Xie, S.: MBA-RAG: a bandit approach for adaptive retrieval-augmented generation through question complexity. In: Proceedings of COLING 2025, pp. 3248\u20133254 (2025)"},{"key":"40_CR9","first-page":"1","volume-title":"Proceedings of ICLR 2023","author":"T Khot","year":"2023","unstructured":"Khot, T., et al.: Decomposed prompting: a modular approach for solving complex tasks. In: Proceedings of ICLR 2023, pp. 1\u201313 (2023)"},{"key":"40_CR10","unstructured":"Kadavath, S., et al.: Language models (mostly) know what they know. CoRR abs\/2207.05221 (2022)"},{"key":"40_CR11","first-page":"1","volume":"35","author":"K Meng","year":"2022","unstructured":"Meng, K., Bau, D., Andonian, A., Belinkov, Y.: Locating and editing factual associations in GPT. Adv. Neural Inf. Proces. Syst. 35, 1\u201313 (2022)","journal-title":"Adv. Neural Inf. Proces. Syst."},{"key":"40_CR12","first-page":"27022","volume-title":"Proceedings of ACL 2025","author":"Z Yao","year":"2025","unstructured":"Yao, Z., et al.: SeaKR: self-aware knowledge retrieval for adaptive retrieval augmented generation. In: Proceedings of ACL 2025, pp. 27022\u201327043 (2025)"},{"key":"40_CR13","first-page":"12991","volume-title":"Proceedings of ACL 2024","author":"W Su","year":"2024","unstructured":"Su, W., Tang, Y., Ai, Q., Wu, Z., Liu, Y.: DRAGIN: dynamic retrieval augmented generation based on the real-time information needs of large language models. In: Proceedings of ACL 2024, pp. 12991\u201313013 (2024)"},{"key":"40_CR14","first-page":"1","volume-title":"Proceedings of EMNLP 2016","author":"P Rajpurkar","year":"2016","unstructured":"Rajpurkar, P., Zhang, J., Lopyrev, K., Liang, P.: SQuAD: 100,000+ questions for machine comprehension of text. In: Proceedings of EMNLP 2016, pp. 1\u201313 (2016)"},{"key":"40_CR15","first-page":"1","volume":"7","author":"T Kwiatkowski","year":"2019","unstructured":"Kwiatkowski, T., et al.: Natural questions: a benchmark for question answering research. Trans. Assoc. Computat. Linguist. 7, 1\u201313 (2019)","journal-title":"Trans. Assoc. Computat. Linguist."},{"key":"40_CR16","first-page":"1601","volume-title":"Proceedings of ACL 2017","author":"M Joshi","year":"2017","unstructured":"Joshi, M., Choi, E., Weld, D., Zettlemoyer, L.: TriviaQA: a large scale distantly supervised challenge dataset for reading comprehension. In: Proceedings of ACL 2017, pp. 1601\u20131611 (2017)"},{"key":"40_CR17","first-page":"2369","volume-title":"Proceedings of EMNLP 2018","author":"Z Yang","year":"2018","unstructured":"Yang, Z., et al.: HotpotQA: a dataset for diverse, explainable multi-hop question answering. In: Proceedings of EMNLP 2018, pp. 2369\u20132380 (2018)"},{"key":"40_CR18","first-page":"1","volume-title":"Proceedings of COLING 2020","author":"X Ho","year":"2020","unstructured":"Ho, X., Nguyen, A.-K.D., Sugawara, S., Aizawa, A.: Constructing a multi-hop QA dataset for comprehensive evaluation of reasoning steps. In: Proceedings of COLING 2020, pp. 1\u201313 (2020)"},{"key":"40_CR19","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1162\/tacl_a_00475","volume":"10","author":"H Trivedi","year":"2022","unstructured":"Trivedi, H., Balasubramanian, N., Khot, T., Sabharwal, A.: MuSiQue: Multihop questions via single-hop question composition. Trans. Assoc. Computat. Linguist. 10, 539\u2013554 (2022)","journal-title":"Trans. Assoc. Computat. Linguist."},{"key":"40_CR20","first-page":"1","volume":"25","author":"HW Chung","year":"2024","unstructured":"Chung, H.W., et al.: Scaling instruction-finetuned language models. J. Mach. Learn. Res. 25, 1\u201353 (2024)","journal-title":"J. Mach. Learn. Res."},{"key":"40_CR21","first-page":"6769","volume-title":"Proceedings of EMNLP 2020","author":"V Karpukhin","year":"2020","unstructured":"Karpukhin, V., et al.: Dense passage retrieval for open-domain question answering. In: Proceedings of EMNLP 2020, pp. 6769\u20136781 (2020)"},{"key":"40_CR22","first-page":"10014","volume-title":"Proceedings of ACL 2023","author":"H Trivedi","year":"2023","unstructured":"Trivedi, H., Balasubramanian, N., Khot, T., Sabharwal, A.: Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions. In: Proceedings of ACL 2023, pp. 10014\u201310037 (2023)"},{"key":"40_CR23","unstructured":"Sanh, V., Debut, L., Chaumond, J., Wolf, T.: DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. CoRR abs\/1910.01108 (2019)"},{"key":"40_CR24","volume-title":"Reinforcement Learning: an Introduction","author":"RS Sutton","year":"1998","unstructured":"Sutton, R.S., Barto, A.G.: Reinforcement Learning: an Introduction. MIT Press, Cambridge (1998)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3417-2_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T07:12:02Z","timestamp":1784185922000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3417-2_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,17]]},"ISBN":["9789819234165","9789819234172"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3417-2_40","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,17]]},"assertion":[{"value":"17 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","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":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}