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By leveraging auxiliary information such as semantic attributes, ZSL enhances scalability, reduces data dependency, and improves generalisation. This innovative approach is transforming applications in computervision, Natural Language Processing, healthcare, and more. Auxiliary information can include semantic attributes (e.g.,
SegGPT Many successful approaches from NLP are now being translated into computervision. For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computervision. Finally, the resulting segmentation, along with additional classification information.
SegGPT Many successful approaches from NLP are now being translated into computervision. For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computervision. Finally, the resulting segmentation, along with additional classification information.
Symbolic Music Understanding ( MusicBERT ): MusicBERT is based on the BERT (Bidirectional Encoder Representations from Transformers) NLP model. It addresses issues in traditional end-to-end models, like datascarcity and lack of melody control, by separating lyric-to-template and template-to-melody processes.
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