InfoResearchPeer-reviewedLLM-specific
Risk-Aware Privacy Preservation for LLM Inference
- Published
- Record updated
Summary
Researchers propose Rap-LI, a risk-aware privacy preservation framework for LLM inference services such as ChatGPT. It identifies and labels risky content in user prompts, then applies a risk-aware local differential privacy mechanism to sanitize the text. The authors report an average 51.68% improvement in protection against sensitive information leakage over methods with comparable utility.
Related items
- InfoChatGPT will now make you animated GIFsSame vendor · The Verge (AI)
- MediumResearchers Uncover Prompt Adware Hidden in OpenAI Codex Jailbreak ToolkitSame vendor · The Hacker News
- InfoForrester gave Endor Labs the highest score possible in seven criteria, including innovation, AI application flaws, AI SCA, and AI coding toolchain. | Endor LabsSame vendor · Endor Labs Blog
- InfoUber only fulfilled 4 rides from AI agents last quarterSame vendor · The Verge (AI)
- InfoSam Altman addresses RAM comments: People should ‘put as much as they want in their computers’Same vendor · The Verge (AI)