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Language Models for Text Classification: Is In-Context Learning Enough?
International Conference on Language Resources and EvaluationRecent foundational language models have shown state-of-the-art performance in many NLP tasks in zero- and few-shot settings. An advantage of these models over more standard approaches based on fine-tuning is the ability to understand instructions ...
A. Edwards, José Camacho-Collados
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Pushing The Limit of LLM Capacity for Text Classification
The Web ConferenceIn this era of open-ended language modeling, where task boundaries are gradually fading, an urgent question emerges: have we made significant progress in text classification with the full benefit of LLMs?
Yazhou Zhang +4 more
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Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
Recently, dataless text classification has attracted increasing attention. It trains a classifier using seed words of categories, rather than labeled documents that are expensive to obtain. However, a small set of seed words may provide very limited and noisy supervision information, because many documents contain no seed words or only irrelevant seed ...
Ximing Li +4 more
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Recently, dataless text classification has attracted increasing attention. It trains a classifier using seed words of categories, rather than labeled documents that are expensive to obtain. However, a small set of seed words may provide very limited and noisy supervision information, because many documents contain no seed words or only irrelevant seed ...
Ximing Li +4 more
openaire +1 more source
2020
The users of the Internet increase every moment with increasing population and accessibility of the Internet. With the increase in the number of users of the Internet, the number of controversies, arguments and abuses of all kinds increases. It becomes necessary for social media and other sites to identify toxic content amongst a large number of ...
Sreyan Ghosh +3 more
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The users of the Internet increase every moment with increasing population and accessibility of the Internet. With the increase in the number of users of the Internet, the number of controversies, arguments and abuses of all kinds increases. It becomes necessary for social media and other sites to identify toxic content amongst a large number of ...
Sreyan Ghosh +3 more
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Proceedings of the 7th International Conference on Frontiers of Information Technology, 2009
This paper compares statistical techniques for text classification using Naive Bayes and Support Vector Machines, in context of Urdu language. A large corpus is used for training and testing purpose of the classifiers. However, those classifiers cannot directly interpret the raw dataset, so language specific preprocessing techniques are applied on it ...
Abbas Raza Ali, Maliha Ijaz
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This paper compares statistical techniques for text classification using Naive Bayes and Support Vector Machines, in context of Urdu language. A large corpus is used for training and testing purpose of the classifiers. However, those classifiers cannot directly interpret the raw dataset, so language specific preprocessing techniques are applied on it ...
Abbas Raza Ali, Maliha Ijaz
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2015 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS), 2015
Text-frame classification for video is important prior to text detection and recognition to ensure that the text detection and recognition process is being conducted only for frames that consist of text. Otherwise, detecting and recognizing text on non-text frames will lead to false positive where non-text objects may be mistakenly classified as text ...
Muhamad Jaliluddin Mazlan +2 more
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Text-frame classification for video is important prior to text detection and recognition to ensure that the text detection and recognition process is being conducted only for frames that consist of text. Otherwise, detecting and recognizing text on non-text frames will lead to false positive where non-text objects may be mistakenly classified as text ...
Muhamad Jaliluddin Mazlan +2 more
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Feature selection in text classification
2016 24th Signal Processing and Communication Application Conference (SIU), 2016In recent years, text classification have been widely used. Dimension of text data has increased more and more. Working of almost all classification algorithms is directly related to dimension. In high dimension data set, working of classification algorithms both takes time and occurs over fitting problem.
Sahin, Durmus Ozkan +2 more
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Hybrid Model For Text Classification
2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), 2018Increasing popularity of social media sites (e.g., Twitter, Facebook) leads to the increasing amount of online data. Student's casual talks on these social media sites can be used to know their educational experiences i.e. their worries, opinions, feelings, and emotions about the learning process. However, the main challenge is to analyze this informal
Priyanka Ingole +2 more
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INTELLIGENT NLP-DRIVEN TEXT CLASSIFICATION
International Journal on Artificial Intelligence Tools, 2002Information Retrieval (IR) and NLP-driven Information Extraction (IE) are complementary activities. IR helps in locating specific documents within a huge search space (localization) while IE supports the localization of specific information within a document (extraction or explanation). In application scenarios both capabilities are usually needed. IE
R. Basili, Moschitti, Alessandro
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2007
Bilingual documentation has become a common phenomenon in official institutions and private companies. In this scenario, the categorization of bilingual text is a useful tool. In this paper, different approaches will be proposed to tackle this bilingual classification task.
Jorge Civera, Elsa Cubel, Enrique Vidal
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Bilingual documentation has become a common phenomenon in official institutions and private companies. In this scenario, the categorization of bilingual text is a useful tool. In this paper, different approaches will be proposed to tackle this bilingual classification task.
Jorge Civera, Elsa Cubel, Enrique Vidal
openaire +1 more source