2 citations · 6 across the 7 of their papers we have counts for
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cs.LG2024★ 2 cited
Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data
Zhaomin Wu, Junyi Hou, Yiqun Diao +1
Federated Learning (FL) is an evolving paradigm that enables multiple parties to collaboratively train models without sharing raw data. Among its variants, Vertical Federated Learn…
cs.LG2024
Model-based Large Language Model Customization as Service
Zhaomin Wu, Jizhou Guo, Junyi Hou +3
Prominent Large Language Model (LLM) services from providers like OpenAI and Google excel at general tasks but often underperform on domain-specific applications. Current customiza…
cs.CR2024★ 2 cited
LLM-PBE: Assessing Data Privacy in Large Language Models
Qinbin Li, Junyuan Hong, Chulin Xie +10
Large Language Models (LLMs) have become integral to numerous domains, significantly advancing applications in data management, mining, and analysis. Their profound capabilities in…