{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T11:25:48Z","timestamp":1784287548384,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":48,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/"}],"funder":[{"name":"National Research Foundation of Korea","award":["NRF-2023R1A2C3004176"],"award-info":[{"award-number":["NRF-2023R1A2C3004176"]}]},{"name":"Cultural Service Expansion Technology Development Program","award":["RS-2023-00220195"],"award-info":[{"award-number":["RS-2023-00220195"]}]},{"name":"ICT Creative Consilience Program","award":["IITP-2023-2020-0-01819"],"award-info":[{"award-number":["IITP-2023-2020-0-01819"]}]},{"name":"Voice Phishing Information Collection and Processing and Development of a Big Data Investigation Support System","award":["IITP-2022-0-00653"],"award-info":[{"award-number":["IITP-2022-0-00653"]}]},{"name":"HORIZON EUROPE","award":["101084642"],"award-info":[{"award-number":["101084642"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,21]]},"DOI":"10.1145\/3627673.3680044","type":"proceedings-article","created":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T19:34:11Z","timestamp":1729452851000},"page":"4637-4644","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["LAPIS: Language Model-Augmented Police Investigation System"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0140-1264","authenticated-orcid":false,"given":"Heedou","family":"Kim","sequence":"first","affiliation":[{"name":"Korea University &amp; Police Science Institute, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1984-8982","authenticated-orcid":false,"given":"Dain","family":"Kim","sequence":"additional","affiliation":[{"name":"Korea University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1787-3664","authenticated-orcid":false,"given":"Jiwoo","family":"Lee","sequence":"additional","affiliation":[{"name":"Korea University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6038-8702","authenticated-orcid":false,"given":"Chanwoong","family":"Yoon","sequence":"additional","affiliation":[{"name":"Korea University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8857-9680","authenticated-orcid":false,"given":"Donghee","family":"Choi","sequence":"additional","affiliation":[{"name":"Imperial College London, London, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6458-7723","authenticated-orcid":false,"given":"Mogan","family":"Gim","sequence":"additional","affiliation":[{"name":"Hankuk University of Foreign Studies, Yongin, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6798-9106","authenticated-orcid":false,"given":"Jaewoo","family":"Kang","sequence":"additional","affiliation":[{"name":"Korea University, Seoul, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,10,21]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Korean National Police Agency. 2022. Police statistics data. https:\/\/www.police. go.kr\/www\/open\/publice\/publice0204.jsp"},{"key":"e_1_3_2_2_2_1","volume-title":"AIP Conference Proceedings","volume":"2816","author":"Bag Akash","year":"2024","unstructured":"Akash Bag, Saurav Shashikant, Prateek Mishra, and Ashika Pradhan. 2024. Using artificial intelligence in US law enforcement-a review. In AIP Conference Proceedings, Vol. 2816. AIP Publishing."},{"key":"e_1_3_2_2_3_1","volume-title":"Beyond procedural justice: A dialogic approach to legitimacy in criminal justice. J. Crim. l. & Criminology 102","author":"Bottoms Anthony","year":"2012","unstructured":"Anthony Bottoms and Justice Tankebe. 2012. Beyond procedural justice: A dialogic approach to legitimacy in criminal justice. J. Crim. l. & Criminology 102 (2012), 119."},{"key":"e_1_3_2_2_4_1","unstructured":"Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020. Language models are few-shot learners. Advances in neural information processing systems 33 (2020) 1877--1901."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"crossref","unstructured":"F Oliver Bunnin and Jim Q Smith. 2021. A Bayesian hierarchical model for criminal investigations. (2021).","DOI":"10.1214\/19-BA1192"},{"key":"e_1_3_2_2_6_1","volume-title":"The criminal investigation process: A summary report. Policy Analysis","author":"Chaiken Jan M","year":"1977","unstructured":"Jan M Chaiken, Peter W Greenwood, and Joan Petersilia. 1977. The criminal investigation process: A summary report. Policy Analysis (1977), 187--217."},{"key":"e_1_3_2_2_7_1","volume-title":"ChatGPT may Pass the Bar Exam soon, but has a Long Way to Go for the LexGLUE benchmark. arXiv preprint arXiv:2304.12202","author":"Chalkidis Ilias","year":"2023","unstructured":"Ilias Chalkidis. 2023. ChatGPT may Pass the Bar Exam soon, but has a Long Way to Go for the LexGLUE benchmark. arXiv preprint arXiv:2304.12202 (2023)."},{"key":"e_1_3_2_2_8_1","volume-title":"Daniel Martin Katz, and Nikolaos Aletras","author":"Chalkidis Ilias","year":"2021","unstructured":"Ilias Chalkidis, Abhik Jana, Dirk Hartung, Michael Bommarito, Ion Androutsopoulos, Daniel Martin Katz, and Nikolaos Aletras. 2021. LexGLUE: A benchmark dataset for legal language understanding in English. arXiv preprint arXiv:2110.00976 (2021)."},{"key":"e_1_3_2_2_9_1","volume-title":"Ai assistance in legal analysis: An empirical study. Available at SSRN 4539836","author":"Choi Jonathan H","year":"2023","unstructured":"Jonathan H Choi and Daniel Schwarcz. 2023. Ai assistance in legal analysis: An empirical study. Available at SSRN 4539836 (2023)."},{"key":"e_1_3_2_2_10_1","first-page":"1","article-title":"Palm: Scaling language modeling with pathways","volume":"24","author":"Chowdhery Aakanksha","year":"2023","unstructured":"Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2023. Palm: Scaling language modeling with pathways. Journal of Machine Learning Research 24, 240 (2023), 1--113.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_11_1","volume-title":"Handbook of criminal investigation","author":"Clark Denis","unstructured":"Denis Clark. 2012. Covert surveillance and informer handling. In Handbook of criminal investigation. Willan, 452--475."},{"key":"e_1_3_2_2_12_1","volume-title":"Large legal fictions: Profiling legal hallucinations in large language models. arXiv preprint arXiv:2401.01301","author":"Dahl Matthew","year":"2024","unstructured":"Matthew Dahl, Varun Magesh, Mirac Suzgun, and Daniel E Ho. 2024. Large legal fictions: Profiling legal hallucinations in large language models. arXiv preprint arXiv:2401.01301 (2024)."},{"key":"e_1_3_2_2_13_1","volume-title":"QLoRA: efficient finetuning of quantized LLMs","author":"Dettmers Tim","year":"2023","unstructured":"Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2023. QLoRA: efficient finetuning of quantized LLMs (2023). arXiv preprint arXiv:2305.14314 (2023)."},{"key":"e_1_3_2_2_14_1","volume-title":"The faiss library. arXiv preprint arXiv:2401.08281","author":"Douze Matthijs","year":"2024","unstructured":"Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazar\u00e9, Maria Lomeli, Lucas Hosseini, and Herv\u00e9 J\u00e9gou. 2024. The faiss library. arXiv preprint arXiv:2401.08281 (2024)."},{"key":"e_1_3_2_2_15_1","unstructured":"Ivar Andre Fahsing. 2016. The making of an expert detective: Thinking and deciding in criminal investigations. (2016)."},{"key":"e_1_3_2_2_16_1","volume-title":"Decoding the threat landscape: Chatgpt, fraudgpt, and wormgpt in social engineering attacks. arXiv preprint arXiv:2310.05595","author":"Falade Polra Victor","year":"2023","unstructured":"Polra Victor Falade. 2023. Decoding the threat landscape: Chatgpt, fraudgpt, and wormgpt in social engineering attacks. arXiv preprint arXiv:2310.05595 (2023)."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3444369"},{"key":"e_1_3_2_2_18_1","volume-title":"Large language models are reasoning teachers. arXiv preprint arXiv:2212.10071","author":"Ho Namgyu","year":"2022","unstructured":"Namgyu Ho, Laura Schmid, and Se-Young Yun. 2022. Large language models are reasoning teachers. arXiv preprint arXiv:2212.10071 (2022)."},{"key":"e_1_3_2_2_19_1","first-page":"749","article-title":"A framework for the efficient and ethical use of artificial intelligence in the criminal justice system. Fla","volume":"47","author":"Hunter Dan","year":"2019","unstructured":"Dan Hunter, Mirko Bagaric, and Nigel Stobbs. 2019. A framework for the efficient and ethical use of artificial intelligence in the criminal justice system. Fla. St. UL Rev. 47 (2019), 749.","journal-title":"St. UL Rev."},{"key":"e_1_3_2_2_20_1","first-page":"9211","article-title":"Artificial intelligence: advancing automation in forensic science & criminal investigation","volume":"1533","author":"Jadhav Ekta B","year":"2020","unstructured":"Ekta B Jadhav, Mahipal Singh Sankhla, and Rajeev Kumar. 2020. Artificial intelligence: advancing automation in forensic science & criminal investigation. Journal of Seybold Report ISSN NO 1533 (2020), 9211.","journal-title":"Journal of Seybold Report ISSN NO"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3594536.3595170"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9006006"},{"key":"e_1_3_2_2_23_1","volume-title":"Knowledge-augmented reasoning distillation for small language models in knowledge-intensive tasks. Advances in Neural Information Processing Systems 36","author":"Kang Minki","year":"2024","unstructured":"Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, and Sung Ju Hwang. 2024. Knowledge-augmented reasoning distillation for small language models in knowledge-intensive tasks. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_3_2_2_24_1","volume-title":"Shang Gao, and Pablo Arredondo.","author":"Katz Daniel Martin","year":"2023","unstructured":"Daniel Martin Katz, Michael James Bommarito, Shang Gao, and Pablo Arredondo. 2023. Gpt-4 passes the bar exam. Available at SSRN 4389233 (2023)."},{"key":"e_1_3_2_2_25_1","volume-title":"Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks. arXiv preprint arXiv:2404.00376","author":"Kim Hyunjae","year":"2024","unstructured":"Hyunjae Kim, Hyeon Hwang, Jiwoo Lee, Sihyeon Park, Dain Kim, Taewhoo Lee, Chanwoong Yoon, Jiwoong Sohn, Donghee Choi, and Jaewoo Kang. 2024. Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks. arXiv preprint arXiv:2404.00376 (2024)."},{"key":"e_1_3_2_2_26_1","first-page":"13","article-title":"A Named Entity Recognition Model in Criminal Investigation Domain using Pretrained Language Model","volume":"13","author":"Kim Hee-Dou","year":"2022","unstructured":"Hee-Dou Kim and Heuiseok Lim. 2022. A Named Entity Recognition Model in Criminal Investigation Domain using Pretrained Language Model. Journal of the Korea Convergence Society 13, 2 (2022), 13--20.","journal-title":"Journal of the Korea Convergence Society"},{"key":"e_1_3_2_2_27_1","volume-title":"Propile: Probing privacy leakage in large language models. Advances in Neural Information Processing Systems 36","author":"Kim Siwon","year":"2024","unstructured":"Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, and Seong Joon Oh. 2024. Propile: Probing privacy leakage in large language models. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_3_2_2_28_1","unstructured":"Korean Ministry Of Government Legislation. 2023. Korean Law Information Center. https:\/\/www.law.go.kr\/"},{"key":"e_1_3_2_2_29_1","volume-title":"Yegor Klochkov, Muhammad Faaiz Taufiq, and Hang Li.","author":"Liu Yang","year":"2023","unstructured":"Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, and Hang Li. 2023. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models? Alignment. arXiv preprint arXiv:2308.05374 (2023)."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP46215.2023.10179300"},{"key":"e_1_3_2_2_31_1","volume-title":"Teaching small language models to reason. arXiv preprint arXiv:2212.08410","author":"Magister Lucie Charlotte","year":"2022","unstructured":"Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, Eric Malmi, and Aliaksei Severyn. 2022. Teaching small language models to reason. arXiv preprint arXiv:2212.08410 (2022)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3199437"},{"key":"e_1_3_2_2_33_1","volume-title":"Beyond logic programming for legal reasoning. arXiv preprint arXiv:2306.16632","author":"Nguyen Ha-Thanh","year":"2023","unstructured":"Ha-Thanh Nguyen, Francesca Toni, Kostas Stathis, and Ken Satoh. 2023. Beyond logic programming for legal reasoning. arXiv preprint arXiv:2306.16632 (2023)."},{"key":"e_1_3_2_2_34_1","unstructured":"FUNDAMENTALS OF O'HARA'S. 1956. CRIMINAL INVESTIGATION. (1956)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"crossref","unstructured":"Karen McGregor Richmond. 2020. AI machine learning and international criminal investigations: The lessons from forensic science. (2020).","DOI":"10.2139\/ssrn.3727899"},{"key":"e_1_3_2_2_36_1","volume-title":"Handbook of criminal investigation","author":"Roberts Paul","unstructured":"Paul Roberts. 2012. Law and criminal investigation. In Handbook of criminal investigation. Willan, 118--171."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-55180-3_39"},{"key":"e_1_3_2_2_38_1","unstructured":"No seop Park. 2023. Criminal Investigation. The Police Mutual Aid Association."},{"key":"e_1_3_2_2_39_1","volume-title":"Criminal investigation: An introduction to principles and practice","author":"Stelfox Peter","unstructured":"Peter Stelfox. 2013. Criminal investigation: An introduction to principles and practice. Willan."},{"key":"e_1_3_2_2_40_1","volume-title":"Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel ShuWei Ting.","author":"Thirunavukarasu Arun James","year":"2023","unstructured":"Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel ShuWei Ting. 2023. Large language models in medicine. Nature medicine 29, 8 (2023), 1930--1940."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Shubo Tian Qiao Jin Lana Yeganova Po-Ting Lai Qingqing Zhu Xiuying Chen Yifan Yang Qingyu Chen Won Kim Donald C Comeau et al. 2024. Opportunities and challenges for ChatGPT and large language models in biomedicine and health. Briefings in Bioinformatics 25 1 (2024) bbad493.","DOI":"10.1093\/bib\/bbad493"},{"key":"e_1_3_2_2_42_1","volume-title":"Legal prompt engineering for multilingual legal judgement prediction. arXiv preprint arXiv:2212.02199","author":"Trautmann Dietrich","year":"2022","unstructured":"Dietrich Trautmann, Alina Petrova, and Frank Schilder. 2022. Legal prompt engineering for multilingual legal judgement prediction. arXiv preprint arXiv:2212.02199 (2022)."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1093\/police\/paz035"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"crossref","unstructured":"ThomasWolf Lysandre Debut Victor Sanh Julien Chaumond Clement Delangue Anthony Moi Pierric Cistac Tim Rault R\u00e9mi Louf Morgan Funtowicz et al. 2019. Huggingface's transformers: State-of-the-art natural language processing. arXiv preprint arXiv:1910.03771 (2019).","DOI":"10.18653\/v1\/2020.emnlp-demos.6"},{"key":"e_1_3_2_2_45_1","volume-title":"A survey on knowledge distillation of large language models. arXiv preprint arXiv:2402.13116","author":"Xu Xiaohan","year":"2024","unstructured":"Xiaohan Xu, Ming Li, Chongyang Tao, Tao Shen, Reynold Cheng, Jinyang Li, Can Xu, Dacheng Tao, and Tianyi Zhou. 2024. A survey on knowledge distillation of large language models. arXiv preprint arXiv:2402.13116 (2024)."},{"key":"e_1_3_2_2_46_1","volume-title":"On Protecting the Data Privacy of Large Language Models (LLMs): A Survey. arXiv preprint arXiv:2403.05156","author":"Yan Biwei","year":"2024","unstructured":"Biwei Yan, Kun Li, Minghui Xu, Yueyan Dong, Yue Zhang, Zhaochun Ren, and Xiuzheng Cheng. 2024. On Protecting the Data Privacy of Large Language Models (LLMs): A Survey. arXiv preprint arXiv:2403.05156 (2024)."},{"key":"e_1_3_2_2_47_1","volume-title":"Legal prompting: Teaching a language model to think like a lawyer. arXiv preprint arXiv:2212.01326","author":"Yu Fangyi","year":"2022","unstructured":"Fangyi Yu, Lee Quartey, and Frank Schilder. 2022. Legal prompting: Teaching a language model to think like a lawyer. arXiv preprint arXiv:2212.01326 (2022)."},{"key":"e_1_3_2_2_48_1","volume-title":"Ethical ChatGPT: Concerns, challenges, and commandments. arXiv preprint arXiv:2305.10646","author":"Zhou Jianlong","year":"2023","unstructured":"Jianlong Zhou, Heimo M\u00fcller, Andreas Holzinger, and Fang Chen. 2023. Ethical ChatGPT: Concerns, challenges, and commandments. arXiv preprint arXiv:2305.10646 (2023)."}],"event":{"name":"CIKM '24: The 33rd ACM International Conference on Information and Knowledge Management","location":"Boise ID USA","acronym":"CIKM '24","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 33rd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3680044","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3627673.3680044","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:58:17Z","timestamp":1750294697000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3680044"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,21]]},"references-count":48,"alternative-id":["10.1145\/3627673.3680044","10.1145\/3627673"],"URL":"https:\/\/doi.org\/10.1145\/3627673.3680044","relation":{},"subject":[],"published":{"date-parts":[[2024,10,21]]},"assertion":[{"value":"2024-10-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}