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pro vyhledávání: '"low-resource ner"'
Named Entity Recognition (NER) is a fundamental task in NLP that is used to locate the key information in text and is primarily applied in conversational and search systems. In commercial applications, NER or comparable slot-filling methods have been
Externí odkaz:
http://arxiv.org/abs/2306.06477
Autor:
Chen, Xiang, Li, Lei, Deng, Shumin, Tan, Chuanqi, Xu, Changliang, Huang, Fei, Si, Luo, Chen, Huajun, Zhang, Ningyu
Most NER methods rely on extensive labeled data for model training, which struggles in the low-resource scenarios with limited training data. Existing dominant approaches usually suffer from the challenge that the target domain has different label se
Externí odkaz:
http://arxiv.org/abs/2109.00720
Data augmentation is an effective solution to data scarcity in low-resource scenarios. However, when applied to token-level tasks such as NER, data augmentation methods often suffer from token-label misalignment, which leads to unsatsifactory perform
Externí odkaz:
http://arxiv.org/abs/2108.13655
Autor:
Lee, Dong-Ho, Kadakia, Akshen, Tan, Kangmin, Agarwal, Mahak, Feng, Xinyu, Shibuya, Takashi, Mitani, Ryosuke, Sekiya, Toshiyuki, Pujara, Jay, Ren, Xiang
Recent advances in prompt-based learning have shown strong results on few-shot text classification by using cloze-style templates. Similar attempts have been made on named entity recognition (NER) which manually design templates to predict entity typ
Externí odkaz:
http://arxiv.org/abs/2110.08454
In low-resource natural language processing (NLP), the key problems are a lack of target language training data, and a lack of native speakers to create it. Cross-lingual methods have had notable success in addressing these concerns, but in certain c
Externí odkaz:
http://arxiv.org/abs/2006.09627
In low-resource settings, the performance of supervised labeling models can be improved with automatically annotated or distantly supervised data, which is cheap to create but often noisy. Previous works have shown that significant improvements can b
Externí odkaz:
http://arxiv.org/abs/1910.06061
Conference
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Kniha
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Publikováno v:
International Journal of Crowd Science, Vol 8, Iss 3, Pp 140-148 (2024)
In recent years, great success has been achieved in many tasks of natural language processing (NLP), e.g., named entity recognition (NER), especially in the high-resource language, i.e., English, thanks in part to the considerable amount of labeled r
Externí odkaz:
https://doaj.org/article/81d5a7ca26fa4efbbe29919c44fd942c
Conference
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