1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CR2025
Depth Gives a False Sense of Privacy: LLM Internal States Inversion
Tian Dong, Yan Meng, Shaofeng Li +3
Large Language Models (LLMs) are increasingly integrated into daily routines, yet they raise significant privacy and safety concerns. Recent research proposes collaborative inferen…
cs.LG2025
Step-wise Adaptive Integration of Supervised Fine-tuning and Reinforcement Learning for Task-Specific LLMs
Jack Chen, Fazhong Liu, Naruto Liu +7
Large language models (LLMs) excel at mathematical reasoning and logical problem-solving. The current popular training paradigms primarily use supervised fine-tuning (SFT) and rein…
cs.LG2025★ 1 cited
Model Inversion in Split Learning for Personalized LLMs: New Insights from Information Bottleneck Theory
Yunmeng Shu, Shaofeng Li, Tian Dong +2
Personalized Large Language Models (LLMs) have become increasingly prevalent, showcasing the impressive capabilities of models like GPT-4. This trend has also catalyzed extensive r…