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...
Robustness
DPAdapter: A New Technique Designed to Amplify the Model Performance of Differentially Private Machine Learning DPML Algorithms by Enhancing Parameter Robustness
Privacy in machine learning is critical, especially when models are trained on sensitive data. Differential privacy (DP) offers a framework...
