4 papers
AutoNeural: Co-Designing Vision-Language Models for NPU Inference
Wei Chen, Liangmin Wu, Yunhai Hu +9
While Neural Processing Units (NPUs) offer high theoretical efficiency for edge AI, state-of-the-art Vision--Language Models (VLMs) tailored for GPUs often falter on these substrat…
DP-FedLoRA: Privacy-Enhanced Federated Fine-Tuning for On-Device Large Language Models
Honghui Xu, Shiva Shrestha, Wei Chen +2
As on-device large language model (LLM) systems become increasingly prevalent, federated fine-tuning enables advanced language understanding and generation directly on edge devices…
A Survey: Towards Privacy and Security in Mobile Large Language Models
Honghui Xu, Kaiyang Li, Wei Chen +3
Mobile Large Language Models (LLMs) are revolutionizing diverse fields such as healthcare, finance, and education with their ability to perform advanced natural language processing…
OmniVLM: A Token-Compressed, Sub-Billion-Parameter Vision-Language Model for Efficient On-Device Inference
Wei Chen, Zhiyuan Li, Shuo Xin
We present OmniVLM, a sub-billion-parameter vision-language model for efficient on-device inference. OmniVLM introduces a token compression mechanism that reduces visual token sequ…