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Knowl. Discov. Data"],"published-print":{"date-parts":[[2026,5,31]]},"abstract":"<jats:p>Legal Judgment Prediction (LJP) focuses on predicting judgment results based on the facts of cases. While State-of-the-Art (SOTA) methods have shown impressive performance in law article prediction and charge prediction, they still exhibit weaknesses in prison term prediction. One major reason is that existing models fail to mimic human legal quantitative reasoning to understand monetary features in case facts. Consequently, they do not rigorously quantify the severity of the crime, which is essential for prison term prediction. In this article, we explore and explain how to leverage monetary features to improve LJP via quantitative reasoning. Specifically, we propose QR-LJP, a quantitative reasoning-based LJP model, to integrate legal reasoning knowledge into the prediction process. QR-LJP first employs a curated LLM to extract monetary values from case facts and uses legal quantitative reasoning logic to determine the total crime amount, serving as the quantitative measure of the crime\u2019s severity. This measure is subsequently used to make judgment predictions. We evaluate our model on the real-world dataset CAIL-2018. Experimental results demonstrate that our model outperforms current SOTAs, highlighting the effectiveness of legal quantitative reasoning. Moreover, applying our quantitative reasoning strategy to existing SOTA methods yields significant improvements, especially in macro-F1 scores.<\/jats:p>","DOI":"10.1145\/3807945","type":"journal-article","created":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T14:52:14Z","timestamp":1776264734000},"page":"1-42","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Improving Legal Judgment Prediction via Quantitative Reasoning"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-9064-636X","authenticated-orcid":false,"given":"Zhuo","family":"Han","sequence":"first","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3538-5516","authenticated-orcid":false,"given":"Yi","family":"Feng","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4628-620X","authenticated-orcid":false,"given":"Yi","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9270-5072","authenticated-orcid":false,"given":"Chuanyi","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3166-8525","authenticated-orcid":false,"given":"Zhiwei","family":"Fei","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4751-8798","authenticated-orcid":false,"given":"Xuxing","family":"Ding","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1773-0942","authenticated-orcid":false,"given":"Jidong","family":"Ge","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8237-429X","authenticated-orcid":false,"given":"Vincent","family":"Ng","sequence":"additional","affiliation":[{"name":"Human Language Technology Research Institute, University of Texas at Dallas, Richardson, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,5,19]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.93"},{"key":"e_1_3_2_3_2","unstructured":"Jinze Bai Shuai Bai Yunfei Chu Zeyu Cui Kai Dang Xiaodong Deng Yang Fan Wenbin Ge Yu Han Fei Huang et al. 2023. 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