Legalbench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Language Models are Few-Shot Learners

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372 · see citing works

On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445922 · Cited by 6,988 · see citing works

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., & Zhou, D. (2022) · arXiv · doi:10.48550/arxiv.2201.11903 · Cited by 4,263 · see citing works

GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Wang, A., Singh, A., Michael, J., Hill, F., Levy, O., & Bowman, S. (2018) · Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP · doi:10.18653/v1/w18-5446 · Cited by 4,222 · see citing works

On the Opportunities and Risks of Foundation Models

Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv · doi:10.48550/arxiv.2108.07258 · Cited by 2,676 · see citing works

Llama 2: Open Foundation and Fine-Tuned Chat Models

Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al. (2023) · arXiv · doi:10.48550/arxiv.2307.09288 · Cited by 2,604 · see citing works

Datasheets for Datasets

Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Daumé, H., & Crawford, K. (2018) · arXiv · doi:10.48550/arxiv.1803.09010 · Cited by 2,474

Datasheets for datasets

Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., III, H. D., & Crawford, K. (2021) · Communications of the ACM · doi:10.1145/3458723 · Cited by 2,469 · see citing works

Opportunities and obstacles for deep learning in biology and medicine

Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., et al. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0387 · Cited by 2,310 · see citing works

The Cambridge handbook of thinking and reasoning

Holyoak, K. J., & Morrison, B. (2005) · Cited by 2,133 · see citing works

Introduction to the CoNLL-2002 Shared Task: Language-Independent Named Entity RecognitionPreprint

Sang, E. T. K. (2002) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0209010 · Cited by 1,677 · see citing works

The PASCAL Recognising Textual Entailment Challenge

Dagan, I., Glickman, O., & Magnini, B. (2006) · Lecture notes in computer science · doi:10.1007/11736790_9 · Cited by 1,674 · see citing works

Evaluating Large Language Models Trained on Code

Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. D. O., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., et al. (2021) · arXiv · doi:10.48550/arxiv.2107.03374 · Cited by 1,436 · see citing works

WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex InstructionsPreprint

Xu, C., Sun, Q., Zheng, K., Geng, X.-B., Zhao, P., Feng, J., Tao, C., Lin, Q.-W., & Jiang, D. (2023) · International Conference on Learning Representations · doi:10.48550/arxiv.2304.12244 · Cited by 1,362 · see citing works

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Dao, T., Fu, D. Y., Ermon, S., Rudra, A., & Ré, C. (2022) · arXiv · doi:10.48550/arxiv.2205.14135 · Cited by 1,214 · see citing works

SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems

Wang, A., Pruksachatkun, Y., Nangia, N., Singh, A., Michael, J., Hill, F., Levy, O., & Bowman, S. R. (2019) · arXiv · doi:10.48550/arxiv.1905.00537 · Cited by 1,051 · see citing works

Neural Network Acceptability Judgments

Warstadt, A., Singh, A., & Bowman, S. R. (2019) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00290 · Cited by 984 · see citing works

The biggest lie on the Internet: ignoring the privacy policies and terms of service policies of social networking services

Obar, J. A., & Oeldorf-Hirsch, A. (2020) · Information, Communication & Society · doi:10.1080/1369118x.2018.1486870 · Cited by 771 · see citing works

Training Verifiers to Solve Math Word Problems

Cobbe, K., Kosaraju, V., Bavarian, M., Chen, M., Jun, H., Kaiser, L., Plappert, M., Tworek, J., Hilton, J., Nakano, R., et al. (2021) · arXiv · doi:10.48550/arxiv.2110.14168 · Cited by 575 · see citing works

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv · doi:10.48550/arxiv.2206.04615 · Cited by 569 · see citing works

Holistic Evaluation of Language Models

Bommasani, R., Liang, P., & Lee, T. (2023) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.15007 · Cited by 480 · see citing works

Does Anyone Read the Fine Print? Consumer Attention to Standard-Form Contracts

Bakos, Y., Marotta-Wurgler, F., & Trossen, D. R. (2014) · The Journal of Legal Studies · doi:10.1086/674424 · Cited by 436 · see citing works

Untitled work

(2021) · International Conference on Learning Representations · Cited by 435 · see citing works

Legal Judgment Prediction via Topological Learning

Zhong, H., Guo, Z., Tu, C., Xiao, C., Liu, Z., & Sun, M. (2018) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d18-1390 · Cited by 369 · see citing works

Learning to Predict Charges for Criminal Cases with Legal Basis

Luo, B., Feng, Y., Xu, J., Zhang, X., & Zhao, D. (2017) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d17-1289 · Cited by 329 · see citing works

The Creation and Analysis of a Website Privacy Policy Corpus

Wilson, S., Schaub, F., Dara, A. A., Liu, F., Cherivirala, S., Leon, P. G., Andersen, M. S., Zimmeck, S., Sathyendra, K. M., Russell, N. C., et al. (2016) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p16-1126 · Cited by 283 · see citing works

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Suzgun, M., Scales, N., Schärli, N., Gehrmann, S., Tay, Y., Chung, H. W., Chowdhery, A., Le, Q., Chi, E., Zhou, D., et al. (2023) · Findings of the Association for Computational Linguistics: ACL 2023 · doi:10.18653/v1/2023.findings-acl.824 · Cited by 253 · see citing works

CLAUDETTE: an automated detector of potentially unfair clauses in online terms of service

Lippi, M., Pałka, P., Contissa, G., Lagioia, F., Micklitz, H., Giovanni Sartor, B., & Torroni, P. (2019) · Artificial Intelligence and Law · doi:10.1007/s10506-019-09243-2 · Cited by 240 · see citing works

True Few-Shot Learning with Language Models

Perez, E., Kiela, D., & Cho, K. (2021) · arXiv · doi:10.48550/arxiv.2105.11447 · Cited by 226 · see citing works

Text summarization from legal documents: a survey

Kanapala, A., Pal, S., & Pamula, R. (2017) · Artificial Intelligence Review · doi:10.1007/s10462-017-9566-2 · Cited by 194 · see citing works

Untitled work

(2019) · bepress Legal Repository · Cited by 192 · see citing works

Deep learning in law: early adaptation and legal word embeddings trained on large corpora

Chalkidis, I., & Kampas, D. (2018) · Artificial Intelligence and Law · doi:10.1007/s10506-018-9238-9 · Cited by 190 · see citing works

MAPS: Scaling Privacy Compliance Analysis to a Million Apps

Zimmeck, S., Story, P., Smullen, D., Ravichander, A., Wang, Z., Reidenberg, J. R., Russell, N. C., & Sadeh, N. (2019) · Proceedings on Privacy Enhancing Technologies · doi:10.2478/popets-2019-0037 · Cited by 177 · see citing works

ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation

Malik, V., Sanjay, R., Nigam, S. K., Ghosh, K., Guha, S. K., Bhattacharya, A., & Modi, A. (2021) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/2021.acl-long.313 · Cited by 176 · see citing works

The Litigation State Public Regulation and Private Lawsuits in the United States

Farhang, S. (2010) · doi:10.1515/9781400836789 · Cited by 168 · see citing works

The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only

Penedo, G., Malartic, Q., Hesslow, D., Cojocaru, R., Cappelli, A., Alobeidli, H., Pannier, B., Almazrouei, E., & Launay, J. (2023) · arXiv · doi:10.48550/arxiv.2306.01116 · Cited by 164 · see citing works

Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback

Peng, B., Galley, M., He, P., Cheng, H., Xie, Y., Hu, Y., Huang, Q., Liden, L., Yu, Z., Chen, W., et al. (2023) · arXiv · doi:10.48550/arxiv.2302.12813 · Cited by 156 · see citing works

Hungry Hungry Hippos: Towards Language Modeling with State Space Models

Fu, D. Y., Dao, T., Saab, K. K., Thomas, A. W., Rudra, A., & Ré, C. (2022) · arXiv · doi:10.48550/arxiv.2212.14052 · Cited by 123 · see citing works

NLP Based Latent Semantic Analysis for Legal Text Summarization

Merchant, K., & Pande, Y. (2018) · International Conference on Advances in Computing, Communications and Informatics (ICACCI) · doi:10.1109/icacci.2018.8554831 · Cited by 120 · see citing works

A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges

Cui, J., Shen, X., & Wen, S. (2023) · IEEE Access · doi:10.1109/access.2023.3317083 · Cited by 117 · see citing works

LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

Chalkidis, I., Jana, A., Hartung, D., Bommarito, M. J., Androutsopoulos, I., Katz, D. M., & Aletras, N. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3936759 · Cited by 111 · see citing works

Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age

Zataraín, J. M. N. (2018) · SCRIPTed A Journal of Law Technology & Society · doi:10.2966/scrip.150118.156 · Cited by 103 · see citing works

Question Answering for Privacy Policies: Combining Computational and Legal Perspectives

Ravichander, A., Black, A. W., Wilson, S., Norton, T. B., & Sadeh, N. (2019) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d19-1500 · Cited by 103 · see citing works

ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts

Koreeda, Y., & Manning, C. D. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.164 · Cited by 102 · see citing works

The No Reading Problem in Consumer Contract Law

Ayres, I., & Schwartz, A. (2013) · eYLS (Yale Law School) · Cited by 97 · see citing works

Hyena Hierarchy: Towards Larger Convolutional Language Models

Poli, M., Massaroli, S., Nguyen, E., Fu, D. Y., Dao, T., Baccus, S., Bengio, Y., Ermon, S., & Ré, C. (2023) · arXiv · doi:10.48550/arxiv.2302.10866 · Cited by 96 · see citing works

Natural Language Processing in the Legal DomainPreprint

Hartung, D., Katz, D. M., Bommarito, M. J., Gerlach, L., Jana, A., & Soh, J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4336224 · Cited by 92 · see citing works

Rethinking the field of automatic prediction of court decisions

Medvedeva, M., Wieling, M. B., & Vols, M. (2022) · Artificial Intelligence and Law · doi:10.1007/s10506-021-09306-3 · Cited by 89 · see citing works

Overview and Discussion of the Competition on Legal Information Extraction/Entailment (COLIEE) 2021

Rabelo, J. C. B., Goebel, R. G., Kim, M., Kano, Y., Yoshioka, M., & Satoh, K. (2022) · The Review of Socionetwork Strategies · doi:10.1007/s12626-022-00105-z · Cited by 89 · see citing works

MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer

Chalkidis, I., Fergadiotis, M., & Androutsopoulos, I. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.559 · Cited by 89 · see citing works

Ask Me Anything: A simple strategy for prompting language modelsPreprint

Arora, S., Narayan, A., Chen, M. F., Orr, L., Guha, N., Bhatia, K., Chami, I., Sala, F., & Ré, C. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2210.02441 · Cited by 84 · see citing works

Campaign Finance and American Democracy

Dawood, Y. A. (2015) · Annual Review of Political Science · doi:10.1146/annurev-polisci-010814-104523 · Cited by 80 · see citing works

AI Assistance in Legal Analysis: An Empirical Study

Choi, J. H., & Schwarcz, D. (2023) · doi:10.2139/ssrn.4539836 · Cited by 80 · see citing works

Revisiting Transformer-based Models for Long Document Classification

Dai, X., Chalkidis, I., Darkner, S., & Elliott, D. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.534 · Cited by 76 · see citing works

Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark

Niklaus, J., Chalkidis, I., & Stuermer, M. (2021) · Natural Legal Language Processing Workshop (NLLP) · doi:10.18653/v1/2021.nllp-1.3 · Cited by 70 · see citing works

Selective annotation makes language models better few-shot learners

Su, H., Kasai, J., Wu, C. H., Shi, W., Wang, T., Xin, J., Zhang, R., Ostendorf, M., Zettlemoyer, L., Smith, N. A., et al. (2022) · arXiv · doi:10.48550/arxiv.2209.01975 · Cited by 70 · see citing works

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Henderson, P., Krass, M., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. (2022) · Advances in Neural Information Processing Systems 35 · doi:10.52202/068431-2119 · Cited by 62 · see citing works

ChatGPT may Pass the Bar Exam soon, but has a Long Way to Go for the LexGLUE benchmarkPreprint

Chalkidis, I. (2023) · Social Science Research Network · doi:10.2139/ssrn.4385460 · Cited by 57 · see citing works

LeSICiN: A Heterogeneous Graph-Based Approach for Automatic Legal Statute Identification from Indian Legal Documents

Paul, S., Goyal, P., & Ghosh, S. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i10.21363 · Cited by 53 · see citing works

LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal Domain

Niklaus, J., Matoshi, V., Rani, P., Galassi, A., Stürmer, M., & Chalkidis, I. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023 · doi:10.18653/v1/2023.findings-emnlp.200 · Cited by 50 · see citing works

Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset

Henderson, P., Krass, M. S., Zheng, L., Guha, N., Manning, C. D., Jurafsky, D., & Ho, D. E. (2022) · arXiv · doi:10.48550/arxiv.2207.00220 · Cited by 49 · see citing works

LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development

Chalkidis, I., Garneau, N., Goanță, C., Katz, D. M., & Søgaard, A. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.865 · Cited by 48 · see citing works

Semantic Segmentation of Legal Documents via Rhetorical Roles

Malik, V., Sanjay, R., Guha, S. K., Hazarika, A., Nigam, S. K., Bhattacharya, A., & Modi, A. (2022) · Natural Legal Language Processing Workshop (NLLP) · doi:10.18653/v1/2022.nllp-1.13 · Cited by 48 · see citing works

Oral Arguments Before the Supreme Court

Wrightsman, L. S. (2008) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195368628.001.0001 · Cited by 48 · see citing works

Bootleg: Chasing the Tail with Self-Supervised Named Entity DisambiguationPreprint

Orr, L., Leszczynski, M., Arora, S., Wu, S., Guha, N., Xiao, L., & Ré, C. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.10363 · Cited by 48 · see citing works

RAFT: A Real-World Few-Shot Text Classification BenchmarkPreprint

Alex, N., Lifland, E., Tunstall, L., Thakur, A., Maham, P., Riedel, C. J., Hine, E., Ashurst, C., Sedille, P., Carlier, A., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.14076 · Cited by 47 · see citing works

Exploring the Effectiveness of Prompt Engineering for Legal Reasoning Tasks

Yu, F., Quartey, L., & Schilder, F. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.858 · Cited by 47 · see citing works

Legal Judgment Prediction: A Survey of the State of the Art

Feng, Y., Li, C., & Ng, V. (2022) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2022/765 · Cited by 44 · see citing works

Modeling law search as prediction

Dadgostari, F., Guim, M., Beling, P. A., Livermore, M. A., & Rockmore, D. N. (2020) · Artificial Intelligence and Law · doi:10.1007/s10506-020-09261-5 · Cited by 39 · see citing works

FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing

Chalkidis, I., Pasini, T., Zhang, S., Tomada, L., Schwemer, S. F., & Søgaard, A. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.301 · Cited by 36 · see citing works

A Dataset for Statutory Reasoning in Tax Law Entailment and Question AnsweringPreprint

Holzenberger, N., Blair-Stanek, A., & Durme, B. V. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.05257 · Cited by 34 · see citing works

Legal Prompting: Teaching a Language Model to Think Like a LawyerPreprint

Yu, F., Quartey, L., & Schilder, F. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2212.01326 · Cited by 34 · see citing works

Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities EmergencePreprint

Nay, J. J., Karamardian, D., Lawsky, S. B., Tao, W., Bhat, M., Jain, R., Lee, A. T., Choi, J. H., & Kasai, J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4476325 · Cited by 32 · see citing works

Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise?Preprint

Šavelka, J., Ashley, K. D., Gray, M., Westermann, H., & Xu, H. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2306.13906 · Cited by 31 · see citing works

Predicting and understanding law-making with word vectors and an ensemble model

Nay, J. J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0176999 · Cited by 30 · see citing works

Legal Tech, Civil Procedure, and the Future of Adversarialism

Engstrom, D. F., & Gelbach, J. B. (2021) · Penn Carey Law Legal Scholarship Repository (University of Pennsylvania) · Cited by 29 · see citing works

MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding

Wang, S., Scardigli, A., Tang, L., Chen, W., Levkin, D., Chen, A., Ball, S., Woodside, T., Zhang, O. R., & Hendrycks, D. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.1019 · Cited by 26 · see citing works

Multi-granular Legal Topic Classification on Greek Legislation

Papaloukas, C., Chalkidis, I., Athinaios, K., Pantazi, D.-A., & Koubarakis, M. (2021) · Natural Legal Language Processing Workshop (NLLP) · doi:10.18653/v1/2021.nllp-1.6 · Cited by 25 · see citing works

Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularities

Shen, Z., Lo, K., Yu, L., Dahlberg, N., Schlanger, M., & Downey, D. (2022) · neural information processing systems · doi:10.52202/068431-0956 · Cited by 24 · see citing works

A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction

Hwang, W., Lee, D., Cho, K., Lee, H., & Seo, M. (2022) · neural information processing systems · doi:10.52202/068431-2358 · Cited by 24 · see citing works

How to Use Large Language Models for Empirical Legal Research

Choi, J. H. (2024) · Journal of Institutional and Theoretical Economics JITE · doi:10.1628/jite-2024-0006 · Cited by 23 · see citing works

The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications

Süzgün, M., Melas-Kyriazi, L., Sarkar, S. K., Kominers, S. D., & Shieber, S. M. (2023) · neural information processing systems · doi:10.52202/075280-2524 · Cited by 19 · see citing works

The Limitations of Supply Chain Disclosure Regimes

Chilton, A. S., & Sarfaty, G. A. (2016) · bepress Legal Repository · Cited by 18 · see citing works

Predicting Consumer ContractsPreprint

Kolt, N. (2022) · SSRN Electronic Journal · doi:10.15779/z382b8vc90 · Cited by 15 · see citing works

Billions of Parameters Are Worth More Than In-domain Training Data: A case study in the Legal Case Entailment TaskPreprint

Rosa, G., Bonifacio, L., Jeronymo, V., Abonizio, H., Lotufo, R., & Nogueira, R. (2022) · arXiv.org · doi:10.48550/arxiv.2205.15172 · Cited by 15 · see citing works

Legal Case Document Summarization: Extractive and Abstractive Methods and their EvaluationPreprint

Shukla, A., Bhattacharya, P., Poddar, S., Mukherjee, R., Ghosh, K., Goyal, P., & Ghosh, S. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2210.07544 · Cited by 13 · see citing works

Artificial Intelligence for Adjudication: The Social Security Administration and AI GovernancePreprint

Glaze, K., Ho, D. E., Ray, G. K., & Tsang, C. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3935950 · Cited by 11 · see citing works

LegalBench: Prototyping a Collaborative Benchmark for Legal ReasoningPreprint

Guha, N., Ho, D. E., Nyarko, J., & Ré, C. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2209.06120 · Cited by 11 · see citing works

Values Embedded in Legal Artificial Intelligence

Surden, H. (2022) · IEEE Technology and Society Magazine · doi:10.1109/mts.2022.3147542 · Cited by 10 · see citing works

Legal Transformer Models May Not Always HelpPreprint

Geng, S., Lebret, R., & Aberer, K. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.06862 · Cited by 10 · see citing works

Generative InterpretationPreprint

Hoffman, D. A., & Arbel, Y. A. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4526219 · Cited by 10 · see citing works

The Promise of AI in an Open Justice System

Pah, A. R., Schwartz, D. L., Sanga, S., Alexander, C. S., Hammond, K. J., & Amaral, L. A. N. (2022) · AI Magazine · doi:10.1002/aaai.12039 · Cited by 9 · see citing works

Simple Hardware-Efficient Long Convolutions for Sequence ModelingPreprint

Fu, D. Y., Epstein, E. L., Nguyen, E., Thomas, A. W., Zhang, M., Dao, T., Atri Rudra, B., & Ré, C. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2302.06646 · Cited by 9 · see citing works

U-CREAT: Unsupervised Case Retrieval using Events extrAcTion

Joshi, A., Sharma, A., Tanikella, S. K., & Modi, A. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.777 · Cited by 8 · see citing works

How Smart Are Smart Readers? LLMs and the Future of the No-Reading Problem

Arbel, Y. A., & Becher, S. I. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009279079.019 · Cited by 8 · see citing works

The lobbying manual : a complete guide to federal lobbying law and practice

Luneburg, W. V., Susman, T. M., Gordon, R. H., & Practice, R. (2009) · American Bar Association eBooks · Cited by 7 · see citing works

One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial SupportPreprint

Stern, R., Rasiah, V., Matoshi, V., Bose, S. B., Stuermer, M., Chalkidis, I., Ho, D. E., & Niklaus, J. (2023) · arXiv (Cornell University) · doi:10.24451/arbor.19713 · Cited by 7 · see citing works

From Policy Confusion to Doctrinal Clarity: Successor Liability from the Prospective of Big DataPreprint

Fagan, F. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2488819 · Cited by 6 · see citing works

Legal Syllogism Prompting: Teaching Large Language Models for Legal Judgment PredictionPreprint

Jiang, C., & Yang, X. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2307.08321 · Cited by 6 · see citing works

A Computational Analysis of Oral Argument in the Supreme CourtPreprint

Dickinson, G. M. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2306.05373 · Cited by 5 · see citing works

Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification

Guha, N., Chen, M. F., Bhatia, K., Mirhoseini, A., Sala, F., & Ré, C. (2023) · neural information processing systems · doi:10.52202/075280-2762 · Cited by 4 · see citing works

Private Enforcement in the StatesPreprint

Zambrano, D. A., Guha, N., Peters, A., & Xia, J. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4365144 · Cited by 3 · see citing works

Shelter Check: Proactively Finding Tax Minimization Strategies via AI

Blair-Stanek, A., Holzenberger, N., & Durme, B. V. (2022) · HAL · Cited by 2 · see citing works

Defeating the Empire of FormsPreprint

Hoffman, D. A. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4334425 · Cited by 2 · see citing works

Breaking News: Drafting Client Alerts to Prepare for PracticePreprint

Silver, C. (2020) · SSRN Electronic Journal · Cited by 1 · see citing works

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805

OPT: Open Pre-trained Transformer Language Models

Zhang, S., Roller, S., Goyal, N., Artetxe, M., Chen, M., Chen, S., Dewan, C., Diab, M., Li, X., Lin, X. V., et al. (2022) · arXiv · doi:10.48550/arxiv.2205.01068

CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review

Hendrycks, D., Burns, C., Chen, A., & Ball, S. (2021) · arXiv · doi:10.48550/arxiv.2103.06268

A Comprehensive Overview of Large Language Models

Naveed, H., Khan, A. U., Qiu, S., Saqib, M., Anwar, S., Usman, M., Akhtar, N., Barnes, N., & Mian, A. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3744746 · Cited by 1,257 · see citing works

GPT-4 passes the bar exam

Katz, D. M., Bommarito, M. J., Gao, S., & Arredondo, P. (2024) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2023.0254 · Cited by 420 · see citing works

A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4

Kalyan, K. S. (2024) · Natural Language Processing Journal · doi:10.1016/j.nlp.2023.100048 · Cited by 335 · see citing works

Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models

Dahl, M., Magesh, V., Suzgun, M., & Ho, D. E. (2024) · Journal of Legal Analysis · doi:10.1093/jla/laae003 · Cited by 288 · see citing works

Hallucination‐Free? Assessing the Reliability of Leading <scp>AI</scp> Legal Research Tools

Magesh, V., Surani, F., Dahl, M., Suzgun, M., Manning, C. D., & Ho, D. E. (2025) · Journal of Empirical Legal Studies · doi:10.1111/jels.12413 · Cited by 182 · see citing works

Large Language Models on Graphs: A Comprehensive Survey

Jin, B., Liu, G., Han, C., Jiang, M., Ji, H., & Han, J. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2024.3469578 · Cited by 204 · see citing works

CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering

Wiratunga, N., Abeyratne, R., Jayawardena, L., Martin, K., Massie, S., Nkisi-Orji, I., Weerasinghe, R., Liret, A., & Fleish, B. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-63646-2_29 · Cited by 136 · see citing works

Datasets for large language models: a comprehensive survey

Liu, Y., Cao, J., Liu, C., Ding, K., & Jin, L. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11403-7 · Cited by 159 · see citing works

(A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice

Cheong, I., Xia, K., Feng, K. J. K., Chen, Q. Z., & Zhang, A. X. (2024) · The 2024 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3630106.3659048 · Cited by 91 · see citing works

The role of large language models in agriculture: harvesting the future with LLM intelligence

Shaikh, T. A., Rasool, T., Veningston, K., & Yaseen, S. M. (2024) · Progress in Artificial Intelligence · doi:10.1007/s13748-024-00359-4 · Cited by 61 · see citing works

From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents

Chandra, M., Naik, S., Ford, D., Okoli, E., De Choudhury, M., Ershadi, M., Ramos, G., Hernandez, J., Bhattacharjee, A., Warreth, S., et al. (2025) · Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3715275.3732063 · Cited by 44 · see citing works

Hardware Design and Verification with Large Language Models: A Scoping Review, Challenges, and Open Issues

Abdollahi, M., Yeganli, S. F., Baharloo, M. M., & Baniasadi, A. (2024) · Electronics · doi:10.3390/electronics14010120 · Cited by 47 · see citing works

Legal Query RAG

Wahidur, R. S. M., Kim, S., Choi, H., Bhatti, D. S., & Lee, H.-N. (2025) · IEEE Access · doi:10.1109/access.2025.3542125 · Cited by 35 · see citing works

From hallucinations to hazards: benchmarking LLMs for hazard analysis in safety-critical systems

Dokas, Ι. M. (2025) · Safety Science · doi:10.1016/j.ssci.2025.107056 · Cited by 30 · see citing works

Large Language Models are legal but they are not: Making the case for a powerful LegalLLM

Jayakumar, T., Farooqui, F., & Farooqui, L. (2023) · Natural Legal Language Processing Workshop (NLLP) · doi:10.18653/v1/2023.nllp-1.22 · Cited by 29 · see citing works

Sociotechnical Implications of Generative Artificial Intelligence for Information Access

Mitra, B., Cramer, H. S. M., & Gurevich, O. (2024) · The information retrieval series · doi:10.1007/978-3-031-73147-1_7 · Cited by 20 · see citing works

Classifying legal interpretations using large language models

Dugac, G., & Altwicker, T. (2025) · Artificial Intelligence and Law · doi:10.1007/s10506-025-09447-9 · Cited by 17 · see citing works

Can GPT Alleviate the Burden of Annotation?

Gray, M., Šavelka, J., Oliver, W. M., & Ashley, K. D. (2023) · Frontiers in artificial intelligence and applications · doi:10.3233/faia230961 · Cited by 15 · see citing works

Boosting court judgment prediction and explanation using legal entities

Benedetto, I., Koudounas, A., Vaiani, L., Pastor, E., Cagliero, L., Tarasconi, F., & Baralis, E. (2024) · Artificial Intelligence and Law · doi:10.1007/s10506-024-09397-8 · Cited by 17 · see citing works

Unfair clause detection in terms of service across multiple languages

Galassi, A., Lagioia, F., Jabłonowska, A., & Lippi, M. (2024) · Artificial Intelligence and Law · doi:10.1007/s10506-024-09398-7 · Cited by 14 · see citing works

Prompts and Large Language Models: A New Tool for Drafting, Reviewing and Interpreting Contracts?

Wang, B. T. (2024) · Law Technology and Humans · doi:10.5204/lthj.3483 · Cited by 14 · see citing works

Can large language models generate geospatial code?

Hou, S., Shen, Z., Liang, J., Jiao, H., Zhao, A., Qing, Y., Peng, D., Gui, Z., Guan, X., Xiang, L., et al. (2025) · Geo-spatial Information Science · doi:10.1080/10095020.2025.2535523 · Cited by 17 · see citing works

Cross-Domain Knowledge Transfer without Retraining to Facilitating Seamless Knowledge Application in Large Language ModelsPreprint

Kim, J. H., & Kim, H. R. (2024) · Research Square · doi:10.21203/rs.3.rs-4328966/v1 · Cited by 13 · see citing works

Causal Artificial Intelligence in Legal Language Processing: A Systematic Review

Tritto, P. P., & Ponce-Espinosa, H. (2025) · Entropy · doi:10.3390/e27040351 · Cited by 22 · see citing works

Towards AI-Assisted Mapmaking: Assessing the Capabilities of GPT-4o in Cartographic Design

Memduhoğlu, A. (2025) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi14010035 · Cited by 13 · see citing works

Empirical Evaluation of Reasoning LLMs in Machinery Functional Safety Risk Assessment and the Limits of Anthropomorphized Reasoning

Iyenghar, P. (2025) · Electronics · doi:10.3390/electronics14183624 · Cited by 11 · see citing works

Computational Legal Studies Comes of Age

Chau, B. K., & Livermore, M. A. (2024) · European journal of empirical legal studies · doi:10.62355/ejels.19684 · Cited by 11 · see citing works

Leveraging large language models for abstractive summarization of Italian legal news

Benedetto, I., Cagliero, L., Ferro, M., Tarasconi, F., Bernini, C., & Giacalone, G. (2025) · Artificial Intelligence and Law · doi:10.1007/s10506-025-09431-3 · Cited by 12 · see citing works

Artificial intelligence and interspecific law

Gervais, D. J., & Nay, J. J. (2023) · Science · doi:10.1126/science.adi8678 · Cited by 10 · see citing works

The Factuality of Large Language Models in the Legal Domain

Hamdani, R. E., Bonald, T., Malliaros, F. D., Holzenberger, N., & Suchanek, F. M. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679961 · Cited by 11 · see citing works

Benchmarking Large Language Models on Homework Assessment in Circuit Analysis

Chen, L., Qin, Z., Guo, Y., Rohde, J. A., & Zhang, Y. (2025) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-025-00501-w · Cited by 9 · see citing works

tinyBenchmarks: evaluating LLMs with fewer examples

Polo, F. M., Weber, L., Choshen, L., Sun, Y., Xu, G., & Yurochkin, M. (2024) · arXiv · doi:10.48550/arxiv.2402.14992 · Cited by 8 · see citing works

A Systematic Comparison Between Open- and Closed-Source Large Language Models in the Context of Generating GDPR-Compliant Data Categories for Processing Activity Records

von Schwerin, M., & Reichert, M. (2024) · Future Internet · doi:10.3390/fi16120459 · Cited by 8 · see citing works

Identifying open-texture in regulations using LLMs

Guitton, C., Gubelmann, R., Karray, G., Mayer, S., & Tamò‐Larrieux, A. (2025) · Artificial Intelligence and Law · doi:10.1007/s10506-025-09450-0 · Cited by 8 · see citing works

Interacting with AI at Work: Perceptions and Opportunities from the UK Judiciary

Solovey, E., Flanagan, B., & Chen, D. L. (2025) · Annual Symposium on Human-Computer Interaction for Work (CHIWORK) · doi:10.1145/3729176.3729192 · Cited by 8 · see citing works

WIP: Large Language Model-Enhanced Smart Tutor for Undergraduate Circuit Analysis

Chen, L., Xie, H., Rohde, J. A., & Zhang, Y. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328403 · Cited by 8 · see citing works

Bring Retrieval Augmented Generation to Google Gemini via External API: An Evaluation with BIG-Bench DatasetPreprint

Lee, H.-R., & Kim, S. (2024) · Research Square · doi:10.21203/rs.3.rs-4394715/v1 · Cited by 8 · see citing works

The Large Language Model GreekLegalRoBERTa

Saketos, V., Pantazi, D.-A., & Koubarakis, M. (2024) · Hellenic Conference on Artificial Intelligence · doi:10.1145/3688671.3688770 · Cited by 7 · see citing works

Comprehensive Evaluation of AI Hallucination and Novel UV-Oriented Framework toward Safe and Trustworthy AI

Liu, Z., Kou, J., Zhang, W., Gu, C., Fang, X., Huang, Z., Hao, Y., Li, H., Lu, X., Yin, A., et al. (2024) · International Conference on Universal Village (UV) · doi:10.1109/uv63228.2024.11189137 · Cited by 9 · see citing works

A Reusable Prompting Framework for Applying Large Language Models to Legal Tasks

Sriram, S., Vijayaraj, N., Krishna, G. R., Bhanu, S. V., Choudhary, G., & Murugan, T. (2026) · IEEE Access · doi:10.1109/access.2026.3650941 · Cited by 8 · see citing works

LEXam: Benchmarking Legal Reasoning on 340 Law ExamsPreprint

Fan, Y., Ni, J., Merane, J., Salimbeni, E., Tian, Y., Hermstrüwer, Y., Huang, Y., Akhtar, M., Geering, F., Dreyer, O., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5265144 · Cited by 25 · see citing works

Legal knowledge infusion for large language models: A survey

Liu, Q., Yu, H., Wang, Q., Xu, Q., Li, J., Zou, Z., Mao, R., & Cambria, E. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103426 · Cited by 7 · see citing works

LENS: Layers of Evaluation of Hallucination in GenAI Systems

Gu, C., Zhang, W., Huang, Z., Kou, J., Liu, Z., Zhao, C., Liu, C., Zhang, L., Lin, W., Wang, Z., et al. (2024) · International Conference on Universal Village (UV) · doi:10.1109/uv63228.2024.11189150 · Cited by 16 · see citing works

Security and Privacy of Large Language Models: Threat Taxonomy, Ethical Implications, and Governance

Pribisalić, M., & Martinčić-Ipšić, S. (2026) · AI · doi:10.3390/ai7050152 · Cited by 9 · see citing works

Automating public policy: a comparative study of conversational artificial intelligence models and human expertise in crafting briefing notes

Nzobonimpa, S., Savard, J., Caron, I., & Lawarée, J. (2024) · AI & Society · doi:10.1007/s00146-024-02103-x · Cited by 6 · see citing works

ElecBench: A large language model benchmark in electric power domain

Zhang, S., Huang, Q., Zhang, Q., Liang, X. M., Liu, W., Gao, K., Zhou, F., & Shi, C. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112310 · Cited by 6 · see citing works

Never Start from Scratch: Expediting On-Device LLM Personalization via Explainable Model Selection

Wang, H., Yang, B., Yin, X., & Gao, W. (2025) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/3711875.3729132 · Cited by 5 · see citing works

WisWheat: A Three-Tiered Vision-Language Dataset for Wheat Management

Yuan, B., Song, S., Fernández, J. A., Luo, Y., Baktashmotlagh, M., & Huang, Z. H. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3758256 · Cited by 5 · see citing works

DesignRepair: Dual-Stream Design Guideline-Aware Frontend Repair with Large Language Models

Yuan, M., Chen, J., Xing, Z., Quigley, A. J., Luo, Y., Luo, T., Mohammadi, G., Lu, Q., & Zhu, L. (2025) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1109/icse55347.2025.00109 · Cited by 8 · see citing works

The Law and NLP: Bridging Disciplinary Disconnects

Mahari, R., Stammbach, D., Ash, E., & Pentland, A. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.224 · Cited by 8 · see citing works

GongBu: Easily Fine-tuning LLMs for Domain-specific Adaptation

Zhang, B., Tian, Y., Wang, S., Tu, Z., Chu, D., & Shen, Z. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679233 · Cited by 5 · see citing works

Empower LlaMa 2 for Advanced Logical Reasoning in Natural Language UnderstandingPreprint

Watanabe, N., Kinasaka, K., & Nakamura, A. (2024) · Research Square · doi:10.21203/rs.3.rs-4333417/v1 · Cited by 5 · see citing works

Exploring Brazil's LLM Fauna: Investigating the Generative Performance of Large Language Models in Portuguese

Assis, G., Freitas, C., & Paes, A. (2025) · Journal of the Brazilian Computer Society · doi:10.5753/jbcs.2025.5814 · Cited by 5 · see citing works

Orchestrating Human-AI Teams: The Manager Agent as aUnifying Research Challenge

Masters, C., Vellanki, A., Shangguan, J., Kultys, B., Gilmore, J., Moore, A. P., & Albrecht, S. V. (2025) · International Conference on Distributed Artificial Intelligence (DAI) · doi:10.1145/3772429.3772439 · Cited by 6 · see citing works

From single-agent to multi-agent: a comprehensive review of LLM-based legal agents

Yang, S., Yang, Z., Liu, Y., & Wang, H. (2025) · AI Agent · doi:10.20517/aiagent.2025.06 · Cited by 4 · see citing works

What is the Best Model? Application-Driven Evaluation for Large Language Models

Lian, S., Zhao, K., Liu, X., Lei, X., Yang, B., Zhang, W., Wang, K., & Liu, Z. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-9437-9_6 · Cited by 4 · see citing works

Extractive Summarization of Indian Legal Judgments: Bridging NLP and Generative AI for Socially Responsible Content Generation

Prabhakar, P., & Pati, P. B. (2024) · Studies in computational intelligence · doi:10.1007/978-981-97-8460-8_15 · Cited by 4 · see citing works

Advancing prompt-based language models in the legal domain: adaptive strategies and research challenges

Sheik, R., Reji, S. A., Sharon, A., Avisha, M., & Nirmala, S. J. (2025) · Artificial Intelligence and Law · doi:10.1007/s10506-025-09459-5 · Cited by 5 · see citing works

Capturing Legal Reasoning Paths from Facts to Law in Court Judgments using Knowledge Graphs

Kondo, R., Matsuoka, R., Yoshida, T., Yamasawa, K., & Hisano, R. (2025) · International Conference on Knowledge Capture · doi:10.1145/3731443.3771354 · Cited by 4 · see citing works

Transforming Legal Workflows: A Deep Dive into NLP Solutions for Legal Challenges

Irfan, H., Peerzada, S., & Mansoor, M. (2024) · International Conference on Emerging Technologies · doi:10.1109/icet63392.2024.10935072 · Cited by 3 · see citing works

Legal Hallucinations and the Adoption of Artificial Intelligence in the Judiciary

Herrera-Tapias, B. A., & Guzmán, D. H. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.03.158 · Cited by 7 · see citing works

The European Court of Justice Dataset: Legal Issues and Doctrine

Šadl, U., Brekke, S. A., Zurita, L. L., & Kim, E. H. (2025) · Journal of law & empirical analysis. · doi:10.1177/2755323x251337809 · Cited by 3 · see citing works

Towards a Corpus Methodology for LLMs in the Legal Domain

Athaydes, A., Mota, L. B. B., Neto, F. H. D. A. M., da Silva, S. R., Mane, B., Claro, D. B., Souza, M., & Lisboa, A. B. C. (2025) · Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL) · doi:10.5753/stil.2025.37831 · Cited by 3 · see citing works

Precedent Aware Legal Reasoning System for Turkish Jurisdiction with RAG Supported LLMs

Genç, U., Keskin, Ö. F., Akman, N. P., Berkol, A., & Birant, D. (2025) · International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) · doi:10.1109/ismsit67332.2025.11267996 · Cited by 4 · see citing works

AI for Statutory Simplification: A Comprehensive State Legal Corpus and Labor Benchmark

Hariri, E., & Ho, D. E. (2025) · International Conference on Artificial Intelligence and Law · doi:10.1145/3769126.3769256 · Cited by 5 · see citing works

Dolomites : Domain-Specific Long-Form Methodical Tasks

Malaviya, C., Agrawal, P., Ganchev, K., Srinivasan, P., Huot, F., Berant, J., Yatskar, M., Das, D., Lapata, M., & Alberti, C. (2024) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00727 · Cited by 6 · see citing works

ReguloGPT: Harnessing GPT for End-to-End Knowledge Graph Construction of Molecular Regulatory Pathways

Wu, X., Jo, S., Zeng, Y., Das, A., Zhang, T., Patel, P. S., Wei, Y., Li, L., Gao, S., Zhang, J., et al. (2024) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi62660.2024.10913581 · Cited by 3 · see citing works

Expiration vs. Termination

Mhia-Alddin, D. A., & Hussein, A. M. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-4862-9.ch002 · Cited by 3 · see citing works

Unveiling the Potential of Large Language Models

Varghese, N., & Ramasamy, G. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-5288-5.ch015 · Cited by 3 · see citing works

XtremeLLMs: Towards Extremely Large Language ModelsPreprint

Mienye, I. D., Swart, T. G., & Obaido, G. (2024) · Preprints.org · doi:10.20944/preprints202408.1483.v1 · Cited by 3 · see citing works

Introduction to the special issue on applications and evaluation of large language models in the legal domain

Conrad, J. G., Ganguly, D., Ghosh, K., & Ghosh, S. (2025) · Artificial Intelligence and Law · doi:10.1007/s10506-025-09487-1 · Cited by 3 · see citing works

Large language models: applications, limitations, challenges, and recommendations in cybersecurity, digital forensics, and ethical hacking

Yaacoub, J.-P. A., Noura, H., Salman, O., & Pujolle, G. (2025) · Annals of Telecommunications · doi:10.1007/s12243-025-01134-9 · Cited by 2 · see citing works

Automatic Legal Writing Evaluation of LLMs

Pires, R., Malaquias, R. D., & Nogueira, R. (2025) · International Conference on Artificial Intelligence and Law · doi:10.1145/3769126.3769227 · Cited by 7 · see citing works

Using Large Language Models to Automate Annotation and Part-of-Math Tagging of Math Equations

Shan, R., & Youssef, A. S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-66997-2_1 · Cited by 2 · see citing works

Multilingual Scraper of Privacy Policies and Terms of Service

Bernhard, D., Nenadic, L., Bechtold, S., & Kubíček, K. (2025) · doi:10.1145/3709025.3712215 · Cited by 2 · see citing works

Software engineering meets legal texts: LLMs for auto detection of contract smells

Dechtiar, M., Katz, D. M., & Wang, H. (2025) · Machine Learning with Applications · doi:10.1016/j.mlwa.2025.100639 · Cited by 4 · see citing works

Unifying Corroborative and Contributive Attributions in Large Language Models

Worledge, T., Shen, J. H., Meister, N., Winston, C., & Guestrin, C. (2024) · IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) · doi:10.1109/satml59370.2024.00039 · Cited by 2 · see citing works

Designing for the Future of Information Access with Generative Information Retrieval

Murdock, V., Lee, C., & Hersh, W. (2024) · The information retrieval series · doi:10.1007/978-3-031-73147-1_9 · Cited by 1 · see citing works

LLM Non-text-focused Data Generation for Payroll Fraud Detection

Ouesleti, F., ElBedoui, K., Barhoumi, W., & Aissaoui, M. A. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-7238-7_26 · Cited by 1 · see citing works

The Cocoruta Hub: Open and Curated Corpora, Datasets and Language Models on Brazilian Ocean Law

Santo, F. O. D. E., Peres, S. M., Gonçalves, B., Ortega, F. J. M., Matos, V. B., de Lima, A. P., Brandão, A. A. F., & Cozman, F. G. (2025) · Journal of the Brazilian Computer Society · doi:10.5753/jbcs.2025.5791 · Cited by 1 · see citing works

Enhanced Retrieval-Augmented Generation for Chinese Legal Question Answering

Zhang, S., Sun, W., & Wen, Y. (2025) · International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE) · doi:10.1109/cbase67452.2025.11335575 · Cited by 1 · see citing works

A Domain-specific Hallucination Evaluation Framework for AI Agents in Substation Operation and Maintenance Scenarios

Wang, Z., Li, L., Chen, L., Xu, X., Li, M., & Su, Y. (2025) · International Conference on Wireless Communication, Networking and Internet of Things (WCNIoT) · doi:10.1109/wcniot67424.2025.11381315 · Cited by 1 · see citing works

LLM-assisted formalization for deterministic detection of statutory inconsistency in tax law

Yadamsuren, B., Platt, S. K., & Diaz, M. (2026) · Artificial Intelligence and Law · doi:10.1007/s10506-026-09525-6 · Cited by 1 · see citing works

Retrieval‐Augmented Generation for Large Language Models: Evolution, Architectures, Applications, and Challenges (2020–2025)

Faridi, A. R., Masood, F., Keshvi, & Yunus, T. (2026) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.70122 · Cited by 2 · see citing works

DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain

Huang, E., Sun, P., Wang, S., Lin, Z., Chen, A., Hu, K., Ouyang, J., Li, F., Zhang, Z., Wang, H., et al. (2026) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3770855.3817512 · Cited by 1 · see citing works

Legal Judgement Prediction via Contrastive Learning Based-Retrieval and Semantic Embedding

Wei, C., Zhang, Q., Xu, J., Wang, Y., Huang, Z., & Hao, T. (2024) · IEEE International Symposium on Product Compliance Engineering - Asia (ISPCE-ASIA) · doi:10.1109/ispce-asia64773.2024.10756244 · Cited by 1 · see citing works

Toward a Quantum-Inspired Framework for Modelling Legal Rules

Godfrey, N. (2024) · Quantum Economics and Finance · doi:10.1177/29767032241298302 · Cited by 1 · see citing works

Predicting potentially abusive clauses in Chilean terms of services with natural language processing

Löffler, C., Freile, A. M., & Pizarro, T. R. (2025) · Artificial Intelligence and Law · doi:10.1007/s10506-025-09462-w · Cited by 3 · see citing works

Trustworthiness Evaluation of Large Language Models

Chen, P., & Liu, S. (2025) · Springer eBooks · doi:10.1007/978-3-031-76770-8_12 · Cited by 2 · see citing works

Economy Watchers Survey Provides Datasets and Tasks for Japanese Financial Domain

Suzuki, M., & Sakaji, H. (2025) · International World Wide Web Conference (WWW) · doi:10.1145/3701716.3715304 · Cited by 1 · see citing works

Legal Mitra: Simplified Legal Resources and Guidance Platform

Chikka, K., Chavan, Y., Gupta, A., Trivedi, M., Jawale, S., & Mhatre, S. (2025) · International Conference for Emerging Technology (INCET) · doi:10.1109/incet64471.2025.11140002 · Cited by 1 · see citing works

PhishBENCH: A Benchmark for Legal Tasks Related to Phishing Attacks

Katoikos, I., Kosmopoulos, D., Iglezakis, I., Kiortsi, P., Thomopoulos, G. A., & Fidas, C. A. (2025) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/ictai66417.2025.00198

Legal Compliance Evaluation of Smart Contracts Generated by Large Language Models

Wijayakoon, C., Dong, H., Bandara, H. M. N. D., Tari, Z., & Soin, A. (2025) · IEEE International Conference on Blockchain and Cryptocurrency (ICBC) · doi:10.1109/icbc64466.2025.11114661 · Cited by 3 · see citing works

Measuring What Matters: Developing Human-Centered Legal Q-and-A Quality Standards through Multi-Stakeholder ResearchPreprint

Hagan, M. D. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5146722 · Cited by 1 · see citing works

Benchmarking Multimodal Large Language Models for Forensic Science and Medicine: A Comprehensive Dataset and Evaluation FrameworkPreprint

Sohail, A., Patel, O. P., Choi, J., Venditti, J. C. S., & Wu, A. J. (2025) · medRxiv · doi:10.1101/2025.07.06.25330972 · Cited by 1 · see citing works

A Two-Phase Stability Study of LLM Judges and Bar Council Examiners on Thai Bar-Exam Free-Form Essays

Akarajaradwong, P., Lertprasertphakorn, W., Chaksangchaichot, C., & Nutanong, S. (2026) · arXiv · doi:10.48550/arxiv.2605.25652

Legal NLP Meets MiCAR: Advancing the Analysis of Crypto White Papers

Camassa, C. (2023) · Natural Legal Language Processing Workshop (NLLP) · doi:10.18653/v1/2023.nllp-1.14 · Cited by 2 · see citing works

Professor GPT: Having a Large Language Model Write a Commentary on Freedom of AssemblyPreprint

Engel, C., & Kruse, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4994131

Legal Judgment Prediction Through Argument Analysis

Azmi, Mistica, M., Levy, I., & Hovy, E. H. (2024) · Lecture notes in computer science · doi:10.1007/978-981-96-0348-0_4

The Negotiation Trap An Experiment on a Large Language ModelPreprint

Engel, C. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.5076291

PLawBench: A Rubric-Based Benchmark for Evaluating LLMs in Real-World Legal PracticePreprint

Shi, Y., Liu, H., Hu, Y., Song, G., Xu, X., Ma, Y., Tang, T., Zhang, L., Chen, Q., Feng, D., et al. (2026) · arXiv (Cornell University)

LawBench: Benchmarking Legal Knowledge of Large Language ModelsPreprint

Fei, Z.-W., Shen, X., Zhu, D., Zhou, F., Han, Z., Zhang, S., Chen, K., Shen, Z.-W., & Ge, J.-D. (2023) · arXiv.org · doi:10.48550/arxiv.2309.16289 · Cited by 176 · see citing works

How Do LLMs Understand Legal Philosophy? Diagnosing Legal-Philosophical Reasoning in LLMsPreprint

Zheng, S., Lee, Y., Gao, X., Wu, J., Hu, J., Wang, K. Q., Lin, X., Liu, Q., Xiao, C., & Huang, T. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2610.19427

Unilaw-R1: A Large Language Model for Legal Reasoning with Reinforcement Learning and Iterative Inference

Cai, H., Zhao, S., Zhang, L., Shen, X., Xu, Q., Shen, W., Wen, Z., & Ban, T. (2025) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2025.emnlp-main.915 · Cited by 2 · see citing works

LEXam: Benchmarking Legal Reasoning on 340 Law ExamsPreprint

Fan, Y., Ni, J., Merane, J., Salimbeni, E., Tian, Y., Hermstrüwer, Y., Huang, Y., Akhtar, M., Geering, F., Dreyer, O., et al. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5265144 · Cited by 25 · see citing works