Topic · Artificial Intelligence in Law
Most cited papers in Artificial Intelligence in Law
What are the most cited papers in Artificial Intelligence in Law?
The most cited paper in Artificial Intelligence in Law is "An introduction to case-based reasoning" (Janet L. Kolodner, 1992), with 1,050 citations. Next come "Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective" (814) and "Credit card fraud detection using machine learning techniques: A comparative analysis" (628).
Showing 50 of 100 papers. Every paper with more than 136 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | An introduction to case-based reasoning Janet L. Kolodner · Artificial Intelligence Review | 1992 | 1,050 |
| 2 | Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective Nikolaos Aletras, Dimitrios Tsarapatsanis, Daniel Preoțiuc-Pietro et al. · PeerJ Computer Science | 24 Oct 2016 | 814 |
| 3 | Credit card fraud detection using machine learning techniques: A comparative analysis John O. Awoyemi, Adebayọ Olusọla Adetunmbi, Samuel Adebayo Oluwadare | Oct 2017 | 628 |
| 4 | ChatGPT Goes to Law School Jonathan H. Choi, Kristin E. Hickman, Amy Monahan et al. · SSRN Electronic Journal | 2023 | 503 |
| 5 | Credit Card Fraud Detection Using AdaBoost and Majority Voting Kuldeep Kaur Randhawa, Chu Kiong Loo, Manjeevan Seera et al. · IEEE Access | 2018 | 479 |
| 6 | Online wind turbine fault detection through automated SCADA data analysis A. Zaher, S.D.J. McArthur, David G. Infield et al. · Wind Energy | 20 Jan 2009 | 470 |
| 7 | A general approach for predicting the behavior of the Supreme Court of the United States Daniel Martin Katz, Michael James Bommarito, Josh Blackman · PLoS ONE | 12 Apr 2017 | 465 |
| 8 | On the evaluation of argumentation formalisms Martin W. A. Caminada, Leïla Amgoud · Artificial Intelligence | 4 Mar 2007 | 456 |
| 9 | Rules of Causal Attribution Thomas R. Shultz · Monographs of the Society for Research in Child Development | 1982 | 436 |
| 10 | Knowledge Based Solution Strategies in Medical Reasoning Vimla L. Patel, Guy J. Groen · Cognitive Science | 1986 | 434 |
| 11 | Using machine learning to predict decisions of the European Court of Human Rights Masha Medvedeva, Michel Vols, Martijn Wieling · Artificial Intelligence and Law | 26 Jun 2019 | 428 |
| 12 | Preparing for the future of Artificial Intelligence Alan Bundy · AI & Society | 29 Nov 2016 | 428 |
| 13 | Ethics Guidelines for Trustworthy AI Michel Cannarsa · Cambridge University Press eBooks | 18 Nov 2021 | 413 |
| 14 | The Carneades model of argument and burden of proof Thomas F. Gordon, Henry Prakken, Douglas Walton · Artificial Intelligence | 30 Apr 2007 | 403 |
| 15 | How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence Haoxi Zhong, Chaojun Xiao, Cunchao Tu et al. | 2020 | 355 |
| 16 | Legal Judgment Prediction via Topological Learning Haoxi Zhong, Zhipeng Guo, Cunchao Tu et al. | 2018 | 350 |
| 17 | Watson: Beyond Jeopardy! David A. Ferrucci, Anthony Levas, Sugato Bagchi et al. · Artificial Intelligence | 7 Aug 2012 | 350 |
| 18 | A dialectical model of assessing conflicting arguments in legal reasoning Henry Prakken, Giovanni Sartor · Artificial Intelligence and Law | 1996 | 337 |
| 19 | Argumentation mining Raquel Mochales Palau, Marie‐Francine Moens | 8 Jun 2009 | 317 |
| 20 | Some pedagogical aspects of proof Gila Hanna · Interchange | Mar 1990 | 296 |
| 21 | Turning robotic process automation into commercial success – Case OpusCapita Aleksandre Asatiani, Esko Penttinen · Journal of Information Technology Teaching Cases | 24 May 2016 | 288 |
| 22 | Illuminations and shadows from jury simulations. Shari Seidman Diamond · Law and Human Behavior | Oct 1997 | 282 |
| 23 | Disparate Interactions Ben Green, Yiling Chen | 9 Jan 2019 | 276 |
| 24 | Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models Matthew Dahl, Varun Magesh, Mirac Suzgun et al. · The Journal of Legal Analysis | 2024 | 275 |
| 25 | Lawformer: A pre-trained language model for Chinese legal long documents Chaojun Xiao, Xueyu Hu, Zhiyuan Liu et al. · AI Open | 2021 | 272 |
| 26 | Automatic detection of arguments in legal texts Marie‐Francine Moens, Erik Boiy, Raquel Mochales Palau et al. | 4 Jun 2007 | 265 |
| 27 | A model of legal reasoning with cases incorporating theories and values Trevor J. M. Bench-Capon, Giovanni Sartor · Artificial Intelligence | 22 Jul 2003 | 258 |
| 28 | Process Model Generation from Natural Language Text Fabian Friedrich, Jan Mendling, Frank Puhlmann · Notes on numerical fluid mechanics and multidisciplinary design | 2011 | 250 |
| 29 | Latent Dirichlet allocation (LDA) for topic modeling of the CFPB consumer complaints Kaveh Bastani, Hamed Namavari, Jeffrey Shaffer · Expert Systems with Applications | 7 Mar 2019 | 245 |
| 30 | Can Electronic Clinical Documentation Help Prevent Diagnostic Errors? Gordon D. Schiff, David Westfall Bates · New England Journal of Medicine | 24 Mar 2010 | 245 |
| 31 | REPRESENTING BUSINESS CONTRACTS INRuleML Guido Governatori · International Journal of Cooperative Information Systems | Jun 2005 | 245 |
| 32 | A comparative study of automated legal text classification using random forests and deep learning Haihua Chen, Lei Wu, Jiangping Chen et al. · Information Processing & Management | 17 Nov 2021 | 240 |
| 33 | 'Managing across borders': knowledge management and expatriation in professional service legal firms Jonathan V. Beaverstock · Journal of Economic Geography | 18 Mar 2004 | 239 |
| 34 | Algorithmic justice: Algorithms and big data in criminal justice settings Aleš Završník · European Journal of Criminology | 18 Sep 2019 | 238 |
| 35 | Parallel Tag Clouds to explore and analyze faceted text corpora Christopher M. Collins, Fernanda Viégas, MARTIN P. WATTENBERG | 2009 | 238 |
| 36 | Guided tours and tabletops: tools for communicating in a hypertext environment Randall H. Trigg · ACM Transactions on Information Systems | Oct 1988 | 232 |
| 37 | Performing an Inductive Thematic Analysis of Semi-Structured Interviews With a Large Language Model: An Exploration and Provocation on the Limits of the Approach Stefano De Paoli · Social Science Computer Review | 7 Dec 2023 | 226 |
| 38 | Criminal justice, artificial intelligence systems, and human rights Aleš Završník · ERA Forum | 20 Feb 2020 | 226 |
| 39 | Mock juror sampling issues in jury simulation research: A meta-analysis. Brian H. Bornstein, Jonathan M. Golding, Jeffrey S. Neuschatz et al. · Law and Human Behavior | 20 Oct 2016 | 226 |
| 40 | Algorithmic regulation and the rule of law Mireille Hildebrandt · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences | 6 Aug 2018 | 221 |
| 41 | Learning to Predict Charges for Criminal Cases with Legal Basis Bingfeng Luo, Yansong Feng, Jianbo Xu et al. | 2017 | 220 |
| 42 | GPT-4 passes the bar exam Daniel Martin Katz, Michael James Bommarito, Shang Gao et al. · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences | 25 Feb 2024 | 216 |
| 43 | Foundations for an Electronic Medical Record A. L. Rector, W. Anthony Nowlan, Stephen Kay · Methods of Information in Medicine | 1991 | 214 |
| 44 | AI generates covertly racist decisions about people based on their dialect Valentin Hofmann, Pratyusha Kalluri, Dan Jurafsky et al. · Nature | 28 Aug 2024 | 213 |
| 45 | Modelling Reasoning with Precedents in a Formal Dialogue Game Henry Prakken, Giovanni Sartor | 1998 | 210 |
| 46 | Personalizing Default Rules and Disclosure with Big Data Ariel Porat, Lior Strahilevitz · SSRN Electronic Journal | 2013 | 208 |
| 47 | Psychiatry and the Presumption of Expertise: Flipping Coins in the Courtroom Bruce J. Ennis, Thomas R. Litwack · California Law Review | May 1974 | 206 |
| 48 | The Supreme Court Forecasting Project: Legal and Political Science Approaches to Predicting Supreme Court Decisionmaking Theodore W. Ruger, Pauline T. Kim, Andrew D. Martin et al. · Columbia Law Review | May 2004 | 202 |
| 49 | Text summarization from legal documents: a survey Ambedkar Kanapala, Sukomal Pal, Rajendra Pamula · Artificial Intelligence Review | 29 Jun 2017 | 195 |
| 50 | GENIUS: AN INTEGRATED ENVIRONMENT FOR SUPPORTING THE DESIGN OF GENERIC AUTOMATED NEGOTIATORS Raz Lin, Sarit Kraus, Tim Baarslag et al. · Computational Intelligence | 4 Sep 2012 | 195 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.