Zobrazeno 1 - 10
of 744
pro vyhledávání: '"prompt learning"'
Publikováno v:
The Electronic Library, 2024, Vol. 42, Issue 6, pp. 879-904.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EL-01-2024-0022
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 9, Pp 2349-2360 (2024)
A question-and-answer (Q&A) system for science and technology (S&T) policies and regulations plays a critical role in helping the public understand and apply these regulations. Large language models (LLM) can significantly enhance the accuracy and ef
Externí odkaz:
https://doaj.org/article/9acd47c872ea456b9f41b0b8b0ca3997
Publikováno v:
Data Science and Engineering, Vol 9, Iss 3, Pp 309-324 (2024)
Abstract Personalized review generation is significant for e-commerce applications, such as providing explainable recommendation and assisting the composition of reviews. With the success of pre-trained language models (PLMs), prompt learning-based a
Externí odkaz:
https://doaj.org/article/97f9f69a39d9464e9b87b2a113f128b9
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 2, Pp 547-560 (2024)
Event Extraction (EE) is a key task in information extraction, which requires high-quality annotated data that are often costly to obtain. Traditional classification-based methods suffer from low-resource scenarios due to the lack of label semantics
Externí odkaz:
https://doaj.org/article/bdbb91c1c50043ccb22e91407bd5e58f
Publikováno v:
Visual Computing for Industry, Biomedicine, and Art, Vol 7, Iss 1, Pp 1-13 (2024)
Abstract With recent advancements in robotic surgery, notable strides have been made in visual question answering (VQA). Existing VQA systems typically generate textual answers to questions but fail to indicate the location of the relevant content wi
Externí odkaz:
https://doaj.org/article/aacb44afa9224e1da20c704418d07e75
Publikováno v:
IEEE Access, Vol 12, Pp 123352-123361 (2024)
Few-shot relation extraction uses only limited labeled data to predict relations between entities. Recently, several studies have introduced prompts to better guide models in understanding relations between entities. Although effective, these approac
Externí odkaz:
https://doaj.org/article/2cac701c971e414cbcbf17e1f40af8c3
Publikováno v:
IEEE Access, Vol 12, Pp 13773-13782 (2024)
Hate Speech Detection, aims to identify the widespread presence of harmful speech on social networks, is a long-standing research field. Despite its significance, previous efforts almost focused on English, leading to a notable scarcity of datasets f
Externí odkaz:
https://doaj.org/article/66bffef77113450f8abc32e5f6c47caf
Publikováno v:
Mathematics, Vol 12, Iss 21, p 3359 (2024)
This paper tackles the critical issue of privacy in Natural Language Processing (NLP) systems that process sensitive data by introducing a novel framework combining differential privacy and adversarial training. The proposed solution ensures formal p
Externí odkaz:
https://doaj.org/article/54658be69ee34eab89ae0860c9053548
Publikováno v:
Applied Sciences, Vol 14, Iss 19, p 8719 (2024)
Generative models have shown excellent results in aspect-based sentiment analysis tasks by predicting quadruples by setting specific template formats. The existing research predicts sentiment elements and enhances the dependency between elements usin
Externí odkaz:
https://doaj.org/article/9ce148c7aac847baab334a04d833fa48
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Adverse weather conditions such as rain and haze often lead to a degradation in the quality of maritime images, which is crucial for activities like navigation, fishing, and search and rescue. Therefore, it is of great interest to develop an effectiv
Externí odkaz:
https://doaj.org/article/bf329f1354a642a48922721db7b49a47