Prompt Based NLP

Prompt-based NLP leverages pre-trained language models to perform downstream tasks by framing them as natural language prompts, aiming to improve efficiency and reduce reliance on large labeled datasets. Current research focuses on optimizing prompt design (e.g., schema prompts), mitigating vulnerabilities like backdoor attacks, and enhancing model performance through techniques such as data augmentation and adaptive model training. This approach holds significant promise for advancing low-resource NLP and improving the robustness and generalizability of language models across diverse applications.