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Evaluating Embeddings for One-Shot Classification of Doctor-AI Consultations
By analyzing embeddings such as bag-of-words, character n-grams, Word2Vec, GloVe, fastText, and GPT2 embeddings, we examine how well our one-shot classification systems capture semantic information within medical consultations.
MedAI Dialog Corpus (MEDIC): Zero-Shot Classification of Doctor and AI Responses in Health Consultations
Zero-shot classification enables text to be classified into classes not seen during training.
Legend at ArAIEval Shared Task: Persuasion Technique Detection using a Language-Agnostic Text Representation Model
In this paper, we share our best performing submission to the Arabic AI Tasks Evaluation Challenge (ArAIEval) at ArabicNLP 2023.
Transformer-based approaches to Sentiment Detection
The performance of the four models that were used to detect disaster in the text was compared.
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