#privacy-preserving-inference News & Analysis

SharedRequest: Privacy-Preserving Model-Agnostic Inference for Large Language Models

SharedRequest introduces a privacy-preserving inference framework for large language models that protects user prompt privacy by mixing prompts with noisy variants at the batch level, rather than individual-prompt level. The model-agnostic approach achieves 20% higher utility than differential privacy baselines while reducing query costs by up to 5x, requiring no modifications to LLM architecture.