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相关论文: Rethinking Legal Compliance Automation: Opportunit…

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This research explores the application of Large Language Models (LLMs) for automating the extraction of requirement-related legal content in the food safety domain and checking legal compliance of regulatory artifacts. With Industry 4.0…

软件工程 · 计算机科学 2024-04-29 Shabnam Hassani

Better understanding of Large Language Models' (LLMs) legal analysis abilities can contribute to improving the efficiency of legal services, governing artificial intelligence, and leveraging LLMs to identify inconsistencies in law. This…

Large language models (LLMs) have transformed many fields, including natural language processing, computer vision, and reinforcement learning. These models have also made a significant impact in the field of law, where they are being…

计算与语言 · 计算机科学 2023-03-17 Zhongxiang Sun

Large language models (LLMs) are being increasingly integrated into legal applications, including judicial decision support, legal practice assistance, and public-facing legal services. While LLMs show strong potential in handling legal…

The legal landscape encompasses a wide array of lawsuit types, presenting lawyers with challenges in delivering timely and accurate information to clients, particularly concerning critical aspects like potential imprisonment duration or…

人工智能 · 计算机科学 2024-07-30 Jia-Hong Huang , Chao-Chun Yang , Yixian Shen , Alessio M. Pacces , Evangelos Kanoulas

This chapter explores the application of Large Language Models in the legal domain, showcasing their potential to optimise and augment traditional legal tasks by analysing possible use cases, such as assisting in interpreting statutes,…

计算与语言 · 计算机科学 2025-12-12 Simone Corbo

The increasing complexity of software systems has driven significant advancements in program analysis, as traditional methods unable to meet the demands of modern software development. To address these limitations, deep learning techniques,…

软件工程 · 计算机科学 2025-02-27 Jiayimei Wang , Tao Ni , Wei-Bin Lee , Qingchuan Zhao

The advent of artificial intelligence (AI) has significantly impacted the traditional judicial industry. Moreover, recently, with the development of AI-generated content (AIGC), AI and law have found applications in various domains,…

计算与语言 · 计算机科学 2023-12-08 Jinqi Lai , Wensheng Gan , Jiayang Wu , Zhenlian Qi , Philip S. Yu

With the advancement of Artificial Intelligence (AI) and Large Language Models (LLMs), there is a profound transformation occurring in the realm of natural language processing tasks within the legal domain. The capabilities of LLMs are…

计算与语言 · 计算机科学 2024-04-02 Weicong Qin , Zhongxiang Sun

The rapid development of large language models (LLMs) has not only provided numerous opportunities but also presented significant challenges. This becomes particularly evident when LLMs inadvertently generate harmful or toxic content,…

Large Language Models (LLMs) have significantly advanced the development of Legal Artificial Intelligence (Legal AI) in recent years, enhancing the efficiency and accuracy of legal tasks. To advance research and applications of LLM-based…

计算与语言 · 计算机科学 2025-09-15 Zhitian Hou , Zihan Ye , Nanli Zeng , Tianyong Hao , Kun Zeng

Systematic reviews are crucial for synthesizing scientific evidence but remain labor-intensive, especially when extracting detailed methodological information. Large language models (LLMs) offer potential for automating methodological…

计算与语言 · 计算机科学 2025-10-14 Wenqing Zhang , Trang Nguyen , Elizabeth A. Stuart , Yiqun T. Chen

Interacting with the legal system and the government requires the assembly and analysis of various pieces of information that can be spread across different (paper) documents, such as forms, certificates and contracts (e.g. leases). This…

计算与语言 · 计算机科学 2024-12-23 Hannes Westermann , Jaromir Savelka

Determining which legal cases are relevant to a given query involves navigating lengthy texts and applying nuanced legal reasoning. Traditionally, this task has demanded significant time and domain expertise to identify key Legal Facts and…

人工智能 · 计算机科学 2025-08-15 Shengjie Ma , Qi Chu , Jiaxin Mao , Xuhui Jiang , Haozhe Duan , Chong Chen

Large Language Models (LLMs) could struggle to fully understand legal theories and perform complex legal reasoning tasks. In this study, we introduce a challenging task (confusing charge prediction) to better evaluate LLMs' understanding of…

Recent years have witnessed remarkable progress made in large language models (LLMs). Such advancements, while garnering significant attention, have concurrently elicited various concerns. The potential of these models is undeniably vast;…

计算与语言 · 计算机科学 2023-09-27 Tianhao Shen , Renren Jin , Yufei Huang , Chuang Liu , Weilong Dong , Zishan Guo , Xinwei Wu , Yan Liu , Deyi Xiong

The rapid increase in unstructured data across various fields has made multi-document comprehension and summarization a critical task. Traditional approaches often fail to capture relevant context, maintain logical consistency, and extract…

计算与语言 · 计算机科学 2024-09-30 Aditi Godbole , Jabin Geevarghese George , Smita Shandilya

Privacy law and regulation have turned to "consent" as the legitimate basis for collecting and processing individuals' data. As governments have rushed to enshrine consent requirements in their privacy laws, such as the California Consumer…

软件工程 · 计算机科学 2025-07-08 Aniket Kesari , Travis Breaux , Tom Norton , Sarah Santos , Anmol Singhal

Language models (LMs) are often expected to generate strings in some formal language; for example, structured data, API calls, or code snippets. Although LMs can be tuned to improve their adherence to formal syntax, this does not guarantee…

计算与语言 · 计算机科学 2024-08-06 Terry Koo , Frederick Liu , Luheng He

Problem-solving has been a fundamental driver of human progress in numerous domains. With advancements in artificial intelligence, Large Language Models (LLMs) have emerged as powerful tools capable of tackling complex problems across…

机器学习 · 计算机科学 2025-05-07 Da Zheng , Lun Du , Junwei Su , Yuchen Tian , Yuqi Zhu , Jintian Zhang , Lanning Wei , Ningyu Zhang , Huajun Chen
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