Zobrazeno 1 - 10
of 429
pro vyhledávání: '"Huang, Xiaodi"'
Prevalent solution for BioNER involves using representation learning techniques coupled with sequence labeling. However, such methods are inherently task-specific, demonstrate poor generalizability, and often require dedicated model for each dataset.
Externí odkaz:
http://arxiv.org/abs/2404.17835
As a common approach to learning English, reading comprehension primarily entails reading articles and answering related questions. However, the complexity of designing effective exercises results in students encountering standardized questions, maki
Externí odkaz:
http://arxiv.org/abs/2309.12808
Extracting summaries from long documents can be regarded as sentence classification using the structural information of the documents. How to use such structural information to summarize a document is challenging. In this paper, we propose GoSum, a n
Externí odkaz:
http://arxiv.org/abs/2211.10247
Publikováno v:
In International Journal of Biological Macromolecules December 2024 283 Part 3
Publikováno v:
In Information Fusion February 2025 114
Publikováno v:
In Food Chemistry 15 January 2025 463 Part 3
Publikováno v:
In Information Sciences September 2024 679
Publikováno v:
In Expert Systems With Applications 1 July 2024 245
Autor:
Li, Jiahui, Chen, Wen, Huang, Xiaodi, Hu, Zhiqiang, Duan, Qi, Li, Hongsheng, Metaxas, Dimitris N., Zhang, Shaoting
Weak supervision learning on classification labels has demonstrated high performance in various tasks, while a few pixel-level fine annotations are also affordable. Naturally a question comes to us that whether the combination of pixel-level (e.g., s
Externí odkaz:
http://arxiv.org/abs/2107.00934
Publikováno v:
In Fisheries Research April 2024 272