Awesome-Law-NLP-Research-Work

Summary of NLP related research work in the field of law in recent years, contains paper, competition and some excellent projects, online system.

It will be updated gradually.

Outline

• Outline
  • Paper
  • Competition
  • Online System
  • Question

Paper

   2017

1. Luo B, Feng Y, Xu J, et al. Learning to Predict Charges for Criminal Cases with Legal Basis[C]//Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. 2017: 2727-2736. [PDF]
2. Xiao G, Mo J, Chow E, et al. Multi-Task CNN for classification of Chinese legal questions[C]//2017 IEEE 14th International Conference on e-Business Engineering (ICEBE). IEEE, 2017: 84-90. [PDF]
3. Zhang N, Pu Y F, Yang S Q, et al. An ontological Chinese legal consultation system[J]. IEEE Access, 2017, 5: 18250-18261. [PDF]
4. Xiao G, Chow E, Chen H, et al. Chinese Questions Classification in the Law Domain[C]//2017 IEEE 14th International Conference on e-Business Engineering (ICEBE). IEEE, 2017: 214-219. [PDF]
5. Nazarenko A, Wyner A. Legal NLP Introduction[J]. TAL, 2017, 58: 7-19. [PDF]
6. Sulea O M, Zampieri M, Malmasi S, et al. Exploring the use of text classification in the legal domain[J]. arXiv preprint arXiv:1710.09306, 2017. [PDF]
7. Sulea O M, Zampieri M, Vela M, et al. Predicting the law area and decisions of french supreme court cases[J]. arXiv preprint arXiv:1708.01681, 2017. [PDF]
8. Kanapala A, Pal S, Pamula R. Text summarization from legal documents: a survey[J]. Artificial Intelligence Review, 2019, 51(3): 371-402. [PDF]
9. Hang N T A. Applying deep neural network to retrieve relevant civil law articles[C]//Proceedings of the Student Research Workshop associated with RANLP. 2017: 46-48. [PDF]
10. Do P K, Nguyen H T, Tran C X, et al. Legal question answering using ranking SVM and deep convolutional neural network[J]. arXiv preprint arXiv:1703.05320, 2017. [PDF]

   2018

1. Zhong H, Xiao C, Guo Z, et al. Overview of cail2018: Legal judgment prediction competition[J]. arXiv preprint arXiv:1810.05851, 2018. [PDF]
2. Xiao C, Zhong H, Guo Z, et al. Cail2018: A large-scale legal dataset for judgment prediction[J]. arXiv preprint arXiv:1807.02478, 2018. [PDF]
3. Hu Z, Li X, Tu C, et al. Few-shot charge prediction with discriminative legal attributes[C]//Proceedings of the 27th International Conference on Computational Linguistics. 2018: 487-498. [PDF]
4. Jiang X, Ye H, Luo Z, et al. Interpretable rationale augmented charge prediction system[C]//Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations. 2018: 146-151. [PDF]
5. Ye H, Jiang X, Luo Z, et al. Interpretable Charge Predictions for Criminal Cases: Learning to Generate Court Views from Fact Descriptions[C]//Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018: 1854-1864. [PDF]
6. Zhong H, Guo Z, Tu C, et al. Legal judgment prediction via topological learning[C]//Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2018: 3540-3549. [PDF]
7. Li J, Zhang G, Yan H, et al. A Markov Logic Networks Based Method to Predict Judicial Decisions of Divorce Cases[C]//2018 IEEE International Conference on Smart Cloud (SmartCloud). IEEE, 2018: 129-132. [PDF]
8. Li J, Zhang G, Yu L, et al. Research and Design on Cognitive Computing Framework for Predicting Judicial Decisions[J]. Journal of Signal Processing Systems, 2019, 91(10): 1159-1167. [PDF]
9. Long S, Tu C, Liu Z, et al. Automatic judgment prediction via legal reading comprehension[C]//China National Conference on Chinese Computational Linguistics. Springer, Cham, 2019: 558-572. [PDF]
10. Li P, Zhao F, Li Y, et al. Law text classification using semi-supervised convolutional neural networks[C]//2018 Chinese Control and Decision Conference (CCDC). IEEE, 2018: 309-313. [PDF]
11. Shen Y, Sun J, Li X, et al. Legal article-aware end-to-end memory network for charge prediction[C]//Proceedings of the 2nd International Conference on Computer Science and Application Engineering. 2018: 1-5. [PDF]
12. Merchant K, Pande Y. Nlp based latent semantic analysis for legal text summarization[C]//2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2018: 1803-1807.[PDF]
13. Fawei B, Pan J Z, Kollingbaum M, et al. A methodology for a criminal law and procedure ontology for legal question answering[C]//Joint International Semantic Technology Conference. Springer, Cham, 2018: 198-214. [PDF]
14. Chalkidis I, Kampas D. Deep learning in law: early adaptation and legal word embeddings trained on large corpora[J]. Artificial Intelligence and Law, 2019, 27(2): 171-198. [PDF]
15. Delfino P, Cuconato B, Paulino-Passos G, et al. Using openwordnet-pt for question answering on legal domain[C]//Proceedings of the 9th Global WordNet Conference (GWC 2018). 2018: 106. [PDF]
16. Shen Y, Sun J, Li X, et al. Legal article-aware end-to-end memory network for charge prediction[C]//Proceedings of the 2nd International Conference on Computer Science and Application Engineering. 2018: 1-5. [PDF]
17. Medvedeva M, Vols M, Wieling M. Judicial decisions of the European Court of Human Rights: Looking into the crystal ball[C]//Proceedings of the Conference on Empirical Legal Studies. 2018.
18. Undavia S, Meyers A, Ortega J E. A comparative study of classifying legal documents with neural networks[C]//2018 Federated Conference on Computer Science and Information Systems (FedCSIS). IEEE, 2018: 515-522.
19. Elnaggar A, Gebendorfer C, Glaser I, et al. Multi-task deep learning for legal document translation, summarization and multi-label classification[C]//Proceedings of the 2018 Artificial Intelligence and Cloud Computing Conference. 2018: 9-15.
20. Li S, Zhang H, Ye L, et al. Evaluating the rationality of judicial decision with LSTM-based case modeling[C]//2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). IEEE, 2018: 392-397.

   2019

1. Yang W, Jia W, Zhou X I, et al. Legal judgment prediction via multi-perspective bi-feedback network[J]. arXiv preprint arXiv:1905.03969, 2019. [PDF]
2. 王业沛, 宋梦姣, 王譞, 等. 基于深度学习的判决结果倾向性分析[J]. 计算机应用研究, 2019, 36(2). [PDF]
3. 刘宗林, 张梅山, 甄冉冉, 公佐权, 余南, 付国宏. 融入罪名关键词的法律判决预测多任务学习模型[J]. 清华大学学报（自然科学版）, 2019, 59(7): 497-504. [PDF]
4. 王文广, 陈运文, 蔡华, 曾彦能, 杨慧宇. 基于混合深度神经网络模型的司法文书智能化处理[J]. 清华大学学报（自然科学版）, 2019, 59(7): 505-511. [PDF]
5. 曾道建, 童国维, 戴愿, 李峰, 韩冰, 谢松县. 基于序列到序列模型的法律问题关键词抽取[J]. 清华大学学报（自然科学版）, 2019, 59(4): 256-261. [PDF]
6. Chalkidis I, Androutsopoulos I, Aletras N. Neural Legal Judgment Prediction in English[J]. arXiv preprint arXiv:1906.02059, 2019. [PDF]
7. Wei D, Lin L. An External Knowledge Enhanced Multi-label Charge Prediction Approach with Label Number Learning[J]. arXiv preprint arXiv:1907.02205, 2019. [PDF]
8. Bao Q, Zan H, Gong P, et al. Charge Prediction with Legal Attention[C]//CCF International Conference on Natural Language Processing and Chinese Computing. Springer, Cham, 2019: 447-458. [PDF]
9. Chalkidis I, Fergadiotis M, Malakasiotis P, et al. Large-Scale Multi-Label Text Classification on EU Legislation[J]. arXiv preprint arXiv:1906.02192, 2019. [PDF]
10. Chalkidis I, Fergadiotis M, Malakasiotis P, et al. Extreme multi-label legal text classification: A case study in EU legislation[J]. arXiv preprint arXiv:1905.10892, 2019. [PDF]
11. Li Y, He T, Yan G, et al. Using Case Facts to Predict Penalty with Deep Learning[C]//International Conference of Pioneering Computer Scientists, Engineers and Educators. Springer, Singapore, 2019: 610-617. [PDF]
12. Chen H, Cai D, Dai W, et al. Charge-Based Prison Term Prediction with Deep Gating Network[J]. arXiv preprint arXiv:1908.11521, 2019. [PDF]
13. Xu Z, He T, Lian H, et al. Case Facts Analysis Method Based on Deep Learning[C]//International Conference on Web Information Systems and Applications. Springer, Cham, 2019: 92-97. [PDF]
14. Wang P, Fan Y, Niu S, et al. Hierarchical matching network for crime classification[C]//Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. 2019: 325-334. [PDF]
15. Chen Y S, Chiang S W, Juang T Y. A Few-Shot Transfer Learning Approach Using Text-label Embedding with Legal Attributes for Law Article Prediction[R]. EasyChair, 2019. [PDF]
16. Yang Z, Wang P, Zhang L, et al. A Recurrent Attention Network for Judgment Prediction[C]//International Conference on Artificial Neural Networks. Springer, Cham, 2019: 253-266. [PDF]
17. Chen S, Wang P, Fang W, et al. Learning to Predict Charges for Judgment with Legal Graph[C]//International Conference on Artificial Neural Networks. Springer, Cham, 2019: 240-252. [PDF]
18. Li J, Zhang G, Yu L, et al. Research and Design on Cognitive Computing Framework for Predicting Judicial Decisions[J]. Journal of Signal Processing Systems, 2019, 91(10): 1159-1167. [PDF]
19. Yan G, Li Y, Zhang S, et al. Data Augmentation for Deep Learning of Judgment Documents[C]//International Conference on Intelligent Science and Big Data Engineering. Springer, Cham, 2019: 232-242. [PDF]
20. Liu Z, Tu C, Sun M. Legal Cause Prediction with Inner Descriptions and Outer Hierarchies[C]//China National Conference on Chinese Computational Linguistics. Springer, Cham, 2019: 573-586. [PDF]
21. Yan G, Li Y, Shen S, et al. Law Article Prediction Based on Deep Learning[C]//2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C). IEEE, 2019: 281-284.
22. Li S, Zhang H, Ye L, et al. MANN: A Multichannel Attentive Neural Network for Legal Judgment Prediction[J]. IEEE Access, 2019, 7: 151144-151155.
23. Xiao C, Zhong H, Guo Z, et al. CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain[J]. arXiv preprint arXiv:1911.08962, 2019.
24. Duan X, Wang B, Wang Z, et al. CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension[C]//China National Conference on Chinese Computational Linguistics. Springer, Cham, 2019: 439-451.
25. Bi S, Cheng X, Chen J, et al. Dispute Generation in Law Documents via Joint Context and Topic Attention[C]//Joint International Semantic Technology Conference. Springer, Cham, 2019: 116-129.
26. Pan S, Lu T, Gu N, et al. Charge Prediction for Multi-defendant Cases with Multi-scale Attention[C]//CCF Conference on Computer Supported Cooperative Work and Social Computing. Springer, Singapore, 2019: 766-777.
27. Zhang H, Wang X, Tan H, et al. Applying Data Discretization to DPCNN for Law Article Prediction[C]//CCF International Conference on Natural Language Processing and Chinese Computing. Springer, Cham, 2019: 459-470.
28. Kang L, Liu J, Liu L, et al. Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction[J]. arXiv preprint arXiv:1911.05202, 2019.
29. Zhong H, Xiao C, Tu C, et al. JEC-QA: A Legal-Domain Question Answering Dataset[J]. arXiv preprint arXiv:1911.12011, 2019.
30. Yuan L, Wang J, Fan S, et al. Automatic Legal Judgment Prediction via Large Amounts of Criminal Cases[C]//2019 IEEE 5th International Conference on Computer and Communications (ICCC). IEEE, 2019: 2087-2091.
31. Li S, Liu B, Ye L, et al. Element-Aware Legal Judgment Prediction for Criminal Cases with Confusing Charges[C]//2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2019: 660-667.
32. Visentin A, Nardotto A, O’Sullivan B. Predicting Judicial Decisions: A Statistically Rigorous Approach and a New Ensemble Classifier[C]//2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2019: 1820-1824.
33. Branting K, Weiss B, Brown B, et al. Semi-Supervised Methods for Explainable Legal Prediction[C]//Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law. 2019: 22-31.
34. Kaur A, Bozic B. Convolutional Neural Network-based Automatic Prediction Of Judgments Of The European Court of Human Rights[J]. 2019.
35. Ferro L, Aberdeen J, Branting K, et al. Scalable Methods for Annotating Legal-Decision Corpora[C]//Proceedings of the Natural Legal Language Processing Workshop 2019. 2019: 12-20.
36. Li S, Guo B, Cai Y, et al. Legal Case Inspection: An Analogy-Based Approach to Judgment Evaluation[C]//International Conference on Artificial Intelligence and Security. Springer, Cham, 2019: 148-158.
37. Chitta R, Hudek A K. A Reliable and Accurate Multiple Choice Question Answering System for Due Diligence[C]//Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law. 2019: 184-188.
38. Wang H, He T, Zou Z, et al. Using Case Facts to Predict Accusation Based on Deep Learning[C]//2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C). IEEE, 2019: 133-137.
39. Vacek T, Teo R, Song D, et al. Litigation Analytics: Case outcomes extracted from US federal court dockets[C]//Proceedings of the Natural Legal Language Processing Workshop 2019. 2019: 45-54.
40. Wang Z, Wang B, Duan X, et al. IFlyLegal: A Chinese Legal System for Consultation, Law Searching, and Document Analysis[C]//Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations. 2019: 97-102.
41. Yang X, Shi G, Lou J, et al. Interpretable Charge Prediction with Multi-Perspective Jointly Learning Model[C]//2019 IEEE 5th International Conference on Computer and Communications (ICCC). IEEE, 2019: 1850-1855.
42. Duan X, Zhang Y, Yuan L, et al. Legal Summarization for Multi-role Debate Dialogue via Controversy Focus Mining and Multi-task Learning[C]//Proceedings of the 28th ACM International Conference on Information and Knowledge Management. 2019: 1361-1370.
43. Wang Y, Xu M, Wang L, et al. JEDoDF: Judicial Event Discrimination Based on Deep Forest[C]//2019 15th International Conference on Semantics, Knowledge and Grids (SKG). IEEE, 2019: 36-43.
44. He C, Peng L, Le Y, et al. SECaps: A Sequence Enhanced Capsule Model for Charge Prediction[C]//International Conference on Artificial Neural Networks. Springer, Cham, 2019: 227-239.
45. Bansal N, Sharma A, Singh R K. A Review on the Application of Deep Learning in Legal Domain[C]//IFIP International Conference on Artificial Intelligence Applications and Innovations. Springer, Cham, 2019: 374-381.
46. Bhattacharya P, Ghosh K, Ghosh S, et al. Overview of the FIRE 2019 AILA track: Artificial Intelligence for Legal Assistance[J]. Proc. of FIRE, 2019: 12-15.
47. Bhattacharya P, Paul S, Ghosh K, et al. Identification of Rhetorical Roles of Sentences in Indian Legal Judgments[J]. arXiv preprint arXiv:1911.05405, 2019.

   2020

1. Zhong H, Wang Y, Tu C, et al. Iteratively Questioning and Answering for Interpretable Legal Judgment Prediction[J]. Association for the Advancement of Artificial Intelligence, 2020. [PDF]
2. Li S, Zhang H, Ye L, et al. Prison Term Prediction on Criminal Case Description with Deep Learning[J]. CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 62(3): 1217-1231. [PDF]
3. Shaikh R A, Sahu T P, Anand V. Predicting Outcomes of Legal Cases based on Legal Factors using Classifiers[J]. Procedia Computer Science, 2020, 167: 2393-2402.
4. Xu N, Wang P, Chen L, et al. Distinguish Confusing Law Articles for Legal Judgment Prediction[J]. arXiv preprint arXiv:2004.02557, 2020.
5. Garofalakis J, Plessas K, Plessas A, et al. Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data[J]. Information, 2020, 11(1): 10.
6. Polo F M, Ciochetti I, Bertolo E. Predicting Legal Proceedings Status: an Approach Based on Sequential Text Data[J]. arXiv preprint arXiv:2003.11561, 2020.
7. Polpinij J, Bheganan P, Luaphol B, et al. Identifying of Decision Components in Thai Civil Case Decision by Text Classification Technique[C]//International Conference on Computing and Information Technology. Springer, Cham, 2020: 11-20.
8. Peng, D., Wu, Q. LegalCap: a model for complex case discrimination based on capsule neural network. Soft Comput (2020).
9. Huang Y, Yu Z, Guo J, et al. Legal public opinion news abstractive summarization by incorporating topic information[J]. International Journal of Machine Learning and Cybernetics, 2020: 1-12.
10. Zhong H, Xiao C, Tu C, et al. How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence[J]. arXiv preprint arXiv:2004.12158, 2020.

Competition

• 让AI当法官(BDCI2017), 2017年， 举办单位（明略数据 & 中国计算机学会）[Detail]
• "中国法研杯" ---- 司法人工智能挑战赛(CAIL2018)，2018年，举办单位（中国司法大数据研究院、中国中文信息学会、中电科系统团委联合清华大学、清华大学、北京大学、中国科学院软件研究所）[Detail] [Blog-1] [Blog-2]
• "中国法研杯" ---- 司法人工智能挑战赛(CAIL2019)，2019年
• "中国法研杯" ---- 司法人工智能挑战赛(CAIL2020)，2020年

Online System

• 法信(智答版), 人民法院出版集团、中国司法大数据研究院和北京国双科技有限公司， ---> [法信(智答版)]

• 觅律搜索, 北京幂律智能科技有限责任公司， ---> [觅律so.legal]

• 度小法---法律智库, 百度， ---> [度小法]

• 北大法宝, 北京北大英华科技有限公司、北京大学法制信息中心， ---> [北大法宝]

• 法律智能判决系统, 黑龙江大学自然语言处理实验室， ---> [法律智能判决系统]

• 法小飞, 哈工大讯飞联合实验室， ---> [法小飞-微信公众号]

• 秘塔翻译及智能检索, 秘塔科技， ---> [秘塔翻译及智能检索]

• 包小黑法律咨询, 杭州实在智能科技有限公司， ---> [包小黑法律咨询]