中文
相关论文

相关论文: Explaining Legal Concepts with Augmented Large Lan…

200 篇论文

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

人工智能 · 计算机科学 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

This study investigates judgment prediction in a realistic scenario within the context of Indian judgments, utilizing a range of transformer-based models, including InLegalBERT, BERT, and XLNet, alongside LLMs such as Llama-2 and GPT-3.5…

计算与语言 · 计算机科学 2024-10-15 Shubham Kumar Nigam , Aniket Deroy , Subhankar Maity , Arnab Bhattacharya

Large Language Models (LLMs) have revolutionized the field of Natural Language Processing thanks to their ability to reuse knowledge acquired on massive text corpora on a wide variety of downstream tasks, with minimal (if any) tuning steps.…

计算与语言 · 计算机科学 2024-07-12 Flavio Petruzzellis , Alberto Testolin , Alessandro Sperduti

Grammatical error correction tools are effective at correcting grammatical errors in users' input sentences but do not provide users with \textit{natural language} explanations about their errors. Such explanations are essential for helping…

计算与语言 · 计算机科学 2023-11-17 Yixiao Song , Kalpesh Krishna , Rajesh Bhatt , Kevin Gimpel , Mohit Iyyer

We use the combination of argumentative zoning [1] and a legal argumentative scheme to create legal argumentative segments. Based on the argumentative segmentation, we propose a novel task of classifying argumentative segments of legal case…

计算与语言 · 计算机科学 2023-07-12 Huihui Xu , Kevin Ashley

The advancement of Large Language Models (LLMs), including GPT-4, provides exciting new opportunities for generative design. We investigate the application of this tool across the entire design and manufacturing workflow. Specifically, we…

Generative pre-trained transformer (GPT) models have revolutionized the field of natural language processing (NLP) with remarkable performance in various tasks and also extend their power to multimodal domains. Despite their success, large…

计算与语言 · 计算机科学 2023-08-29 Kaiyuan Gao , Sunan He , Zhenyu He , Jiacheng Lin , QiZhi Pei , Jie Shao , Wei Zhang

Recent advances in the performance of large language models (LLMs) have sparked debate over whether, given sufficient training, high-level human abilities emerge in such generic forms of artificial intelligence (AI). Despite the exceptional…

计算与语言 · 计算机科学 2024-01-18 Nicholas Ichien , Dušan Stamenković , Keith J. Holyoak

Recent advancements in the field of Natural Language Processing, particularly the development of large-scale language models that are pretrained on vast amounts of knowledge, are creating novel opportunities within the realm of Knowledge…

计算与语言 · 计算机科学 2023-10-06 Anisa Rula , Jennifer D'Souza

Large Language Models (LLMs) have demonstrated impressive zero shot performance on a wide range of NLP tasks, demonstrating the ability to reason and apply commonsense. A relevant application is to use them for creating high quality…

计算与语言 · 计算机科学 2024-07-11 Vinay Samuel , Houda Aynaou , Arijit Ghosh Chowdhury , Karthik Venkat Ramanan , Aman Chadha

Large Language Models (LLMs) are widely used in critical fields such as healthcare, education, and finance due to their remarkable proficiency in various language-related tasks. However, LLMs are prone to generating factually incorrect…

The rapid development of language-based artificial intelligence (AI) offers new possibilities for psychotherapy and assistive systems, particularly benefitting autistic individuals who often respond well to technology. Parents of autistic…

The costs and complexity of the American judicial system limit access to legal solutions for many Americans. Large language models (LLMs) hold great potential to improve access to justice. However, a major challenge in applying AI and LLMs…

人工智能 · 计算机科学 2024-10-15 Manuj Kant , Manav Kant , Marzieh Nabi , Preston Carlson , Megan Ma

Generative Pre-trained Transformer 4 (GPT-4) is the fourth-generation language model in the GPT series, developed by OpenAI, which promises significant advancements in the field of natural language processing (NLP). In this research…

计算与语言 · 计算机科学 2023-05-08 Jawid Ahmad Baktash , Mursal Dawodi

In this article, we explore the potential of transformer-based language models (LMs) to correctly represent normative statements in the legal domain, taking tax law as our use case. In our experiment, we use a variety of LMs as bases for…

计算与语言 · 计算机科学 2021-08-26 Reto Gubelmann , Peter Hongler , Siegfried Handschuh

Large Language Models (LLMs), trained on extensive datasets from the web, exhibit remarkable general reasoning skills. Despite this, they often struggle in specialized areas like law, mainly because they lack domain-specific pretraining.…

计算与语言 · 计算机科学 2025-11-27 Mann Khatri , Mirza Yusuf , Rajiv Ratn Shah , Ponnurangam Kumaraguru

E-commerce platforms require structured product data in the form of attribute-value pairs to offer features such as faceted product search or attribute-based product comparison. However, vendors often provide unstructured product…

计算与语言 · 计算机科学 2024-09-23 Alexander Brinkmann , Roee Shraga , Christian Bizer

Large language models~(LLM) like ChatGPT have become indispensable to artificial general intelligence~(AGI), demonstrating excellent performance in various natural language processing tasks. In the real world, graph data is ubiquitous and…

人工智能 · 计算机科学 2023-07-12 Jiayan Guo , Lun Du , Hengyu Liu , Mengyu Zhou , Xinyi He , Shi Han

Large language models (LLMs) have shown remarkable capabilities across a broad range of tasks involving question answering and the generation of coherent text and code. Comprehensively understanding the strengths and weaknesses of LLMs is…

计算与语言 · 计算机科学 2023-06-02 Jonathan Roberts , Timo Lüddecke , Sowmen Das , Kai Han , Samuel Albanie

Large language models (LLMs) perform well at a myriad of tasks, but explaining the processes behind this performance is a challenge. This paper investigates whether LLMs can give faithful high-level explanations of their own internal…

机器学习 · 计算机科学 2024-05-14 Dane Sherburn , Bilal Chughtai , Owain Evans