3 papers
cs.LG2026
Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
Yang Liu, Kejia Zhang, Bingjie Yan +11
Large language models (LMs) offer broad generalization capabilities but require vast amounts of data and computational resources for domain-specific tasks; small models (SMs), in c…
cs.CR2026
From Prompts to Responses: Dual-Sided Data Leakage and Defense in Split Large Language Models
Zixuan Gu, Xiaojun Ye, Yang Liu
Large language models (LLMs) are increasingly deployed in privacy-sensitive domains, where users must balance the risk of data exposure through external APIs against the high compu…
cs.CR2025
VFLAIR-LLM: A Comprehensive Framework and Benchmark for Split Learning of LLMs
Zixuan Gu, Qiufeng Fan, Long Sun +2
With the advancement of Large Language Models (LLMs), LLM applications have expanded into a growing number of fields. However, users with data privacy concerns face limitations in…