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I’m working on a low-resource NLP model for Arabic dialects. How can I improve accuracy with limited labeled data?
Try self-supervised learning techniques like contrastive learning. You can also use transfer learning from MSA (Modern Standard Arabic) models.
That makes sense! Do you have a good paper on adaptive fine-tuning for dialectal NLP?
Sure! Here’s a relevant paper on adaptive fine-tuning:
