Balancing Privacy and Robustness in NLP: A New Approach for Secure Prompt Learning in LLMs

Recent advances in natural language processing (NLP), led by large-scale pre-trained models such as GPT-3 and BERT, have transformed text generation and sentiment analysis tasks. These models’ ability to adapt to various applications with less data has contributed to their popularity in sensitive industries such as healthcare and finance. However, implementing these models creates significant […]

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