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Found 3 papers, 3 papers with code
Using Emotion Embeddings to Transfer Knowledge Between Emotions, Languages, and Annotation Formats
In this work, we study how we can build a single model that can transition between these different configurations by leveraging multilingual models and Demux, a transformer-based model whose input includes the emotions of interest, enabling us to dynamically change the emotions predicted by the model.
Leveraging Label Correlations in a Multi-label Setting: A Case Study in Emotion
First, we develop two modeling approaches to the problem in order to capture word associations of the emotion words themselves, by either including the emotions in the input, or by leveraging Masked Language Modeling (MLM).
Crypto Pump and Dump via Deep Learning Techniques
Despite the fact that cryptocurrencies themselves have experienced an astonishing rate of adoption over the last decade, cryptocurrency fraud detection is a heavily under-researched problem area.
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