{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T08:46:20Z","timestamp":1782204380732,"version":"3.54.5"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031975691","type":"print"},{"value":"9783031975707","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-97570-7_18","type":"book-chapter","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T01:17:25Z","timestamp":1751591845000},"page":"227-243","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["AggTruth: Contextual Hallucination Detection Using Aggregated Attention Scores in\u00a0LLMs"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9282-2892","authenticated-orcid":false,"given":"Piotr","family":"Matys","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0851-1816","authenticated-orcid":false,"given":"Jan","family":"Eliasz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3223-2336","authenticated-orcid":false,"given":"Konrad","family":"Kie\u0142czy\u0144ski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9531-5329","authenticated-orcid":false,"given":"Miko\u0142aj","family":"Langner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3701-3502","authenticated-orcid":false,"given":"Teddy","family":"Ferdinan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7665-6896","authenticated-orcid":false,"given":"Jan","family":"Koco\u0144","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5868-356X","authenticated-orcid":false,"given":"Przemys\u0142aw","family":"Kazienko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,5]]},"reference":[{"key":"18_CR1","doi-asserted-by":"crossref","unstructured":"Azaria, A., et\u00a0al.: The internal state of an LLM knows when it\u2019s lying. In: EMNLP 2023, pp. 967\u2013976. ACL, Singapore (2023)","DOI":"10.18653\/v1\/2023.findings-emnlp.68"},{"key":"18_CR2","doi-asserted-by":"crossref","unstructured":"Chuang, Y.S., et\u00a0al.: Lookback lens: detecting and mitigating contextual hallucinations in large language models using only attention maps (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.84"},{"issue":"8017","key":"18_CR3","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1038\/s41586-024-07421-0","volume":"630","author":"S Farquhar","year":"2024","unstructured":"Farquhar, S., et al.: Detecting hallucinations in large language models using semantic entropy. Nature 630(8017), 625\u2013630 (2024)","journal-title":"Nature"},{"key":"18_CR4","doi-asserted-by":"crossref","unstructured":"Ferdinan, T., et\u00a0al.: Into the unknown: self-learning large language models. In: SENTIRE at ICDM\u20192024, pp. 423\u2013432. IEEE (2024)","DOI":"10.1109\/ICDMW65004.2024.00060"},{"key":"18_CR5","doi-asserted-by":"crossref","unstructured":"Gekhman, Z., et\u00a0al.: Does fine-tuning llms on new knowledge encourage hallucinations? arXiv preprint arXiv:2405.05904 (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.444"},{"key":"18_CR6","unstructured":"Gemma, T., et\u00a0al.: Gemma 2: improving open language models at a practical size. arXiv preprint arXiv:2408.00118 (2024)"},{"key":"18_CR7","unstructured":"Huang, L., et al.: A survey on hallucination in large language models: principles, taxonomy, challenges, and open questions. ACM Trans. Inform. Sys. (2024)"},{"issue":"12","key":"18_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3571730","volume":"55","author":"Z Ji","year":"2023","unstructured":"Ji, Z., et al.: Survey of hallucination in natural language generation. ACM Comput. Surv. 55(12), 1\u201338 (2023)","journal-title":"ACM Comput. Surv."},{"key":"18_CR9","doi-asserted-by":"crossref","unstructured":"Ke, Z., et\u00a0al.: Continual training of language models for few-shot learning. arXiv preprint arXiv:2210.05549 (2022)","DOI":"10.18653\/v1\/2022.emnlp-main.695"},{"key":"18_CR10","doi-asserted-by":"publisher","first-page":"101861","DOI":"10.1016\/j.inffus.2023.101861","volume":"99","author":"J Koco\u0144","year":"2023","unstructured":"Koco\u0144, J., et al.: ChatGPT: jack of all trades, master of none. Inf. Fus. 99, 101861 (2023)","journal-title":"Inf. Fus."},{"key":"18_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v036.i11","volume":"36","author":"MB Kursa","year":"2010","unstructured":"Kursa, M.B., Rudnicki, W.R.: Feature selection with the Boruta package. J. Stat. Softw. 36, 1\u201313 (2010)","journal-title":"J. Stat. Softw."},{"key":"18_CR12","first-page":"452","volume":"7","author":"T Kwiatkowski","year":"2019","unstructured":"Kwiatkowski, T., et al.: Natural questions: a benchmark for question answering research. Trans. ACL 7, 452\u2013466 (2019)","journal-title":"Trans. ACL"},{"key":"18_CR13","unstructured":"Lewis, P., et\u00a0al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. arXiv preprint arXiv:2005.11401 (2021)"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Manakul, P., et\u00a0al.: Selfcheckgpt: zero-resource black-box hallucination detection for generative large language models. arXiv preprint arXiv:2303.08896 (2023)","DOI":"10.18653\/v1\/2023.emnlp-main.557"},{"key":"18_CR15","doi-asserted-by":"crossref","unstructured":"Narayan, S., et\u00a0al.: Don\u2019t give me the details, just the summary! Topic-aware convolutional neural networks for extreme summarization (2018)","DOI":"10.18653\/v1\/D18-1206"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"Peng, B., Alcaide, E., et\u00a0al.: RWKV: reinventing RNNs for the transformer era. In: Findings of the Association for Computational Linguistics: EMNLP 2023 (2023)","DOI":"10.18653\/v1\/2023.findings-emnlp.936"},{"key":"18_CR17","doi-asserted-by":"crossref","unstructured":"See, A., et\u00a0al.: Get to the point: summarization with pointer-generator networks. In: ACL 2017, pp. 1073\u20131083. ACL (2017)","DOI":"10.18653\/v1\/P17-1099"},{"key":"18_CR18","doi-asserted-by":"crossref","unstructured":"Yang, Z., et\u00a0al.: HotpotQA: a dataset for diverse, explainable multi-hop question answering. arXiv preprint arXiv:1809.09600 (2018)","DOI":"10.18653\/v1\/D18-1259"},{"key":"18_CR19","unstructured":"Zhao, W.X., et\u00a0al.: A survey of large language models. arXiv preprint arXiv:2303.18223 (2024)"}],"container-title":["Lecture Notes in Computer Science","Computational Science \u2013 ICCS 2025 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-97570-7_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T18:56:20Z","timestamp":1776884180000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-97570-7_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031975691","9783031975707"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-97570-7_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"5 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Singapore","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 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccs-computsci2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iccs-meeting.org\/iccs2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}