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CLPLM: Character Level Pretrained Language Model for ExtractingSupport Phrases for Sentiment Labels
In this paper, we have designed a character-level pre-trained language model for extracting support phrases from tweets based on the sentiment label.
Analysis of Resource-efficient Predictive Models for Natural Language Processing
In this paper, we presented an analyses of the resource efficient predictive models, namely Bonsai, Binary Neighbor Compression(BNC), ProtoNN, Random Forest, Naive Bayes and Support vector machine(SVM), in the machine learning field for resource constraint devices.
Exploring Multimodal Features and Fusion Strategies for Analyzing Disaster Tweets
Social media platforms, such as Twitter, often provide firsthand news during the outbreak of a crisis.
CMTA: COVID-19 Misinformation Multilingual Analysis on Twitter
To access the performance of the CMTA multilingual model, we performed a comparative analysis of 8 monolingual model and CMTA for the misinformation detection task.
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