Transfer Learning for Power Outage Detection Task with Limited Training Data
The research investigated using transfer learning and language models to detect power outages using limited social media data. While classical models performed best with full training, fine-tuning pre-trained LLMs significantly improved accuracy, achieving up to 81.3% for BERT with minimal data. This shows that few-shot fine-tuning is a powerful technique for outage detection when labeled data is scarce.