15 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.IR2026
Bridging Textual Profiles and Latent User Embeddings for Personalization
Zhaoxuan Tan, Xiang Zhai, Yan Zhu +2
Personalized systems rely on user representations to connect behavioral history with downstream recommendation applications. Existing methods typically employ either supervised lat…
cs.LG2024★ 3 cited
Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices
Ruiyang Qin, Dancheng Liu, Chenhui Xu +9
The scaling laws have become the de facto guidelines for designing large language models (LLMs), but they were studied under the assumption of unlimited computing resources for bot…
cs.CL2023★ 15 cited
Enabling On-Device Large Language Model Personalization with Self-Supervised Data Selection and Synthesis
Ruiyang Qin, Jun Xia, Zhenge Jia +5
After a large language model (LLM) is deployed on edge devices, it is desirable for these devices to learn from user-generated conversation data to generate user-specific and perso…