3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models
Bartłomiej Marek, Lorenzo Rossi, Vincent Hanke +4
Recent work has applied differential privacy (DP) to adapt large language models (LLMs) for sensitive applications, offering theoretical guarantees. However, its practical effectiv…
cs.LG2024★ 3 cited
Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives
Vincent Hanke, Tom Blanchard, Franziska Boenisch +3
While open Large Language Models (LLMs) have made significant progress, they still fall short of matching the performance of their closed, proprietary counterparts, making the latt…