Zobrazeno 1 - 10
of 2 403
pro vyhledávání: '"knowledge aggregation"'
Large language models (LLMs) have shown substantial progress in natural language understanding and generation, proving valuable especially in the medical field. Despite advancements, challenges persist due to the complexity and diversity inherent in
Externí odkaz:
http://arxiv.org/abs/2406.17484
Autor:
Yang, Dejie, Liu, Yang
Accurately detecting active objects undergoing state changes is essential for comprehending human interactions and facilitating decision-making. The existing methods for active object detection (AOD) primarily rely on visual appearance of the objects
Externí odkaz:
http://arxiv.org/abs/2405.12509
Publikováno v:
EMNLP 2023
Abstracts derived from biomedical literature possess distinct domain-specific characteristics, including specialised writing styles and biomedical terminologies, which necessitate a deep understanding of the related literature. As a result, existing
Externí odkaz:
http://arxiv.org/abs/2310.15684
Commonsense knowledge is crucial to many natural language processing tasks. Existing works usually incorporate graph knowledge with conventional graph neural networks (GNNs), resulting in a sequential pipeline that compartmentalizes the encoding proc
Externí odkaz:
http://arxiv.org/abs/2305.06294
Autor:
Wu, Min1 (AUTHOR) madakui_csg@gdcsg.com, Ma, Dakui1 (AUTHOR), Xiong, Kaiqing2 (AUTHOR) xiongkq11@gdcsg.com, Yuan, Linkun2 (AUTHOR) csglinkuny@gdcsg.com
Publikováno v:
Symmetry (20738994). Mar2024, Vol. 16 Issue 3, p322. 15p.
Autor:
Jaus, Alexander, Seibold, Constantin, Hermann, Kelsey, Walter, Alexandra, Giske, Kristina, Haubold, Johannes, Kleesiek, Jens, Stiefelhagen, Rainer
In this study, we present a method for generating automated anatomy segmentation datasets using a sequential process that involves nnU-Net-based pseudo-labeling and anatomy-guided pseudo-label refinement. By combining various fragmented knowledge bas
Externí odkaz:
http://arxiv.org/abs/2307.13375
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Incorporating external graph knowledge into neural chatbot models has been proven effective for enhancing dialogue generation. However, in conventional graph neural networks (GNNs), message passing on a graph is independent from text, resulting in th
Externí odkaz:
http://arxiv.org/abs/2306.16195
Akademický článek
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Mid-term and long-term electric energy demand prediction is essential for the planning and operations of the smart grid system. Mainly in countries where the power system operates in a deregulated environment. Traditional forecasting models fail to i
Externí odkaz:
http://arxiv.org/abs/2212.13913