Towards Robust Legal Reasoning: Harnessing Logical LLMs in Law

Learning information extraction rules: An inductive logic programming approach

James Stuart Aitken. 2002 · 2002

Earlier work this paper cites.

Regulation (eu) 2016/679 of the european parliament and of the council on the protection of natural persons with regard to the processing of personal data and the free movement of such data, and repeal directive 95/46/ec (general data protection regulation)

European Union. 2016 · 2016

Earlier work this paper cites.

Regulation (eu) 2024/1689 of the european parliament and of the council of 13 june 2024 laying down harmonised rules on artificial intelligence and amending regulations (ec) no 300/2008, (eu) no 167/2013, (eu) no 168/2013, (eu) 2018/858, (eu) 2018/1139 and (eu) 2019/2144 and directives 2014/90/eu, (eu) 2016/797 and (eu) 2020/1828 (artificial intelligence act)

European Union. 2024 · 2020

Earlier work this paper cites.

Integrating deep learning with logic fusion for information extraction

Wenya Wang and Sinno Jialin Pan. 2020 · 2020

Earlier work this paper cites.

Legalbench: A collaboratively built benchmark for measuring legal reasoning in large language models

Neel Guha, Julian Nyarko, Daniel E. Ho, Christopher Re, Adam Chilton, Aditya Narayana, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel N. Rockmore, and et al. 2023 · 2023

Earlier work this paper cites.

Toward an ethical human-computer division of labor in law practice

Abdi Aidid. 2024 · 2024

Earlier work this paper cites.

Reliable reasoning beyond natural language

Original

Nasim Borazjanizadeh and Steven Piantadosi. 2024 · 2024

Earlier work this paper cites.

Logically consistent language models via neuro-symbolic integration

Original

Diego Calanzone, Stefano Teso, and Antonio Vergari. 2024 · 2024

Earlier work this paper cites.

Neuro-symbolic ai in 2024: A systematic review

Original

Brandon C. Colelough and William Regli. 2025 · 2024

Earlier work this paper cites.

Large legal fictions: Profiling legal hallucinations in large language models

Matthew Dahl, Varun Magesh, Mirac Suzgun, and Daniel E Ho. 2024 · 2024

Earlier work this paper cites.

Hallucination-free? assessing the reliability of leading ai legal research tools

Original

Varun Magesh, Faiz Surani, Matthew Dahl, Mirac Suzgun, Christopher D. Manning, and Daniel E. Ho. 2024 · 2024

Cited alongside, same era.

Chain of logic: Rule-based reasoning with large language models

Original

Sergio Servantez, Joe Barrow, Kristian Hammond, and Rajiv Jain. 2024 · 2024

Cited alongside, same era.

Logic rules as explanations for legal case retrieval

Original

Zhongxiang Sun, Kepu Zhang, Weijie Yu, Haoyu Wang, and Jun Xu. 2024 · 2024

Cited alongside, same era.

Thought-like-pro: Enhancing reasoning of large language models through self-driven prolog-based chain-of-thought

Original

Xiaoyu Tan, Yongxin Deng, Xihe Qiu, Weidi Xu, Chao Qu, Wei Chu, Yinghui Xu, and Yuan Qi. 2024 · 2024

Cited alongside, same era.

Insurance analyst stanford cardinal care encoding

Stanford CodeX. 2025b · 2025

Closest in time.

SWISH – SWI-Prolog for SHaring

Contributors to SWI-Prolog. 2024 · 2025

Closest in time.

Computable contracts for insurance: Establishing an insurance-specific controlled natural language - insurle

J. Cummins, J. Dávila, R. Kowalski, and D. Ovenden. 2025 · 2025

Closest in time.

Fine-tuning large language models for improving factuality in legal question answering

Original

Yinghao Hu, Leilei Gan, Wenyi Xiao, Kun Kuang, and Fei Wu. 2025 · 2025

Closest in time.

Draft application paper on the supervision of artificial intelligence

International Association of Insurance Supervisors. 2024 · 2025

Closest in time.

Words or code first? Is the legacy document or a code statement the better starting point for complexity-reducing legal automation?