Zobrazeno 1 - 10
of 592
pro vyhledávání: '"Bế Hà Thành"'
Autor:
Nguyen, Hai-Long, Nguyen, Tan-Minh, Nguyen, Duc-Minh, Vuong, Thi-Hai-Yen, Nguyen, Ha-Thanh, Phan, Xuan-Hieu
Statutory law retrieval is a typical problem in legal language processing, that has various practical applications in law engineering. Modern deep learning-based retrieval methods have achieved significant results for this problem. However, retrieval
Externí odkaz:
http://arxiv.org/abs/2410.12154
Reasoning is an essential component of human intelligence as it plays a fundamental role in our ability to think critically, support responsible decisions, and solve challenging problems. Traditionally, AI has addressed reasoning in the context of lo
Externí odkaz:
http://arxiv.org/abs/2410.05339
Computing is still under a significant threat from ransomware, which necessitates prompt action to prevent it. Ransomware attacks can have a negative impact on how smart grids, particularly digital substations. In addition to examining a ransomware d
Externí odkaz:
http://arxiv.org/abs/2405.00418
In this paper, we explore the application of Generative Pre-trained Transformers (GPTs) in cross-lingual legal Question-Answering (QA) systems using the COLIEE Task 4 dataset. In the COLIEE Task 4, given a statement and a set of related legal article
Externí odkaz:
http://arxiv.org/abs/2403.18098
Autor:
Nguyen, Hai-Long, Nguyen, Duc-Minh, Nguyen, Tan-Minh, Nguyen, Ha-Thanh, Vuong, Thi-Hai-Yen, Satoh, Ken
Large language models with billions of parameters, such as GPT-3.5, GPT-4, and LLaMA, are increasingly prevalent. Numerous studies have explored effective prompting techniques to harness the power of these LLMs for various research problems. Retrieva
Externí odkaz:
http://arxiv.org/abs/2403.18093
Autor:
Tran, Vu, Nguyen, Ha-Thanh, Vo, Trung, Luu, Son T., Dang, Hoang-Anh, Le, Ngoc-Cam, Le, Thi-Thuy, Nguyen, Minh-Tien, Nguyen, Truong-Son, Nguyen, Le-Minh
In this new era of rapid AI development, especially in language processing, the demand for AI in the legal domain is increasingly critical. In the context where research in other languages such as English, Japanese, and Chinese has been well-establis
Externí odkaz:
http://arxiv.org/abs/2403.03435
Autor:
Nguyen, Ha-Thanh, Satoh, Ken
Finetuning approaches in NLP often focus on exploitation rather than exploration, which may lead to suboptimal models. Given the vast search space of natural language, this limited exploration can restrict their performance in complex, high-stakes do
Externí odkaz:
http://arxiv.org/abs/2403.01185
This paper presents a deep learning-based system for efficient automatic case summarization. Leveraging state-of-the-art natural language processing techniques, the system offers both supervised and unsupervised methods to generate concise and releva
Externí odkaz:
http://arxiv.org/abs/2312.07824
Language serves as a vehicle for conveying thought, enabling communication among individuals. The ability to distinguish between diverse concepts, identify fairness and injustice, and comprehend a range of legal notions fundamentally relies on logica
Externí odkaz:
http://arxiv.org/abs/2311.13095
Autor:
Nguyen, Hai-Long, Pham, Thi-Kieu-Trang, Le, Thai-Son, Nguyen, Tan-Minh, Vuong, Thi-Hai-Yen, Nguyen, Ha-Thanh
In this study, we present a novel and challenging multilabel Vietnamese dataset (RMDM) designed to assess the performance of large language models (LLMs), in verifying electronic information related to legal contexts, focusing on fake news as potenti
Externí odkaz:
http://arxiv.org/abs/2309.09071