Zobrazeno 1 - 10
of 152
pro vyhledávání: '"Nguyen, Lê Minh"'
In this paper, we propose ZeFaV - a zero-shot based fact-checking verification framework to enhance the performance on fact verification task of large language models by leveraging the in-context learning ability of large language models to extract t
Externí odkaz:
http://arxiv.org/abs/2411.11247
In the Emotion Recognition in Conversation task, recent investigations have utilized attention mechanisms exploring relationships among utterances from intra- and inter-speakers for modeling emotional interaction between them. However, attributes suc
Externí odkaz:
http://arxiv.org/abs/2407.04279
In medical imaging, accurate image segmentation is crucial for quantifying diseases, assessing prognosis, and evaluating treatment outcomes. However, existing methods lack an in-depth integration of global and local features, failing to pay special a
Externí odkaz:
http://arxiv.org/abs/2404.08201
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, Chau, Nguyen, Le-Minh
The objective of legal text entailment is to ascertain whether the assertions in a legal query logically follow from the information provided in one or multiple legal articles. ChatGPT, a large language model, is robust in many natural language proce
Externí odkaz:
http://arxiv.org/abs/2401.17897
Autor:
Nguyen, Chau, Nguyen, Phuong, Tran, Thanh, Nguyen, Dat, Trieu, An, Pham, Tin, Dang, Anh, Nguyen, Le-Minh
The Competition on Legal Information Extraction/Entailment (COLIEE) is held annually to encourage advancements in the automatic processing of legal texts. Processing legal documents is challenging due to the intricate structure and meaning of legal l
Externí odkaz:
http://arxiv.org/abs/2401.03551
Autor:
Sun, Guanqun, Pan, Yizhi, Kong, Weikun, Xu, Zichang, Ma, Jianhua, Racharak, Teeradaj, Nguyen, Le-Minh, Xin, Junyi
Accurate medical image segmentation is critical for disease quantification and treatment evaluation. While traditional Unet architectures and their transformer-integrated variants excel in automated segmentation tasks. However, they lack the ability
Externí odkaz:
http://arxiv.org/abs/2310.12570
Autor:
Nguyen, Phuong Minh, Nguyen, Le Minh
Machine Translation is one of the essential tasks in Natural Language Processing (NLP), which has massive applications in real life as well as contributing to other tasks in the NLP research community. Recently, Transformer -based methods have attrac
Externí odkaz:
http://arxiv.org/abs/2308.10482
Question answering (QA) in law is a challenging problem because legal documents are much more complicated than normal texts in terms of terminology, structure, and temporal and logical relationships. It is even more difficult to perform legal QA for
Externí odkaz:
http://arxiv.org/abs/2306.04841