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Adaptive Name Entity Recognition under Highly Unbalanced Data
For several purposes in Natural Language Processing (NLP), such as Information Extraction, Sentiment Analysis or Chatbot, Named Entity Recognition (NER) holds an important role as it helps to determine and categorize entities in text into predefined groups such as the names of persons, locations, quantities, organizations or percentages, etc.
Label Prediction Framework for Semi-Supervised Cross-Modal Retrieval
In this work, we propose a novel framework in a semi-supervised setting, which can predict the labels of the unlabeled data using complementary information from different modalities.
Semi-Supervised Cross-Modal Retrieval with Label Prediction
Due to abundance of data from multiple modalities, cross-modal retrieval tasks with image-text, audio-image, etc.
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