1 citations · 2 across the 9 of their papers we have counts for
9 papers
PACE: A Unified Condense-and-Extract Paradigm for Fast VLM Inference
Junjie Liu, Shengyuan Ye, Xu Chen
Vision-Language Models (VLMs) demonstrate exceptional visual reasoning capabilities, yet their inference costs escalate rapidly with the proliferation of visual tokens. Existing vi…
Homebot: A Personal AI Agent for Conversational Home Assistance and Automation
Shengyuan Ye, Yixin Zhang, Han Liang +3
\texttt{Homebot} is a locally deployable AI agent for conversational household assistance and automation. It accepts voice and instant-messaging requests through a shared runtime t…
Venus: An Efficient Edge Memory-and-Retrieval System for VLM-based Online Video Understanding
Shengyuan Ye, Bei Ouyang, Tianyi Qian +5
Vision-language models (VLMs) have demonstrated impressive multimodal comprehension capabilities and are being deployed in an increasing number of online video understanding applic…
Jupiter: Fast and Resource-Efficient Collaborative Inference of Generative LLMs on Edge Devices
Shengyuan Ye, Bei Ouyang, Liekang Zeng +4
Generative large language models (LLMs) have garnered significant attention due to their exceptional capabilities in various AI tasks. Traditionally deployed in cloud datacenters,…
Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices
Shengyuan Ye, Liekang Zeng, Xiaowen Chu +2
On-device Deep Neural Network (DNN) training has been recognized as crucial for privacy-preserving machine learning at the edge. However, the intensive training workload and limite…
Resource-Efficient Personal Large Language Models Fine-Tuning with Collaborative Edge Computing
Shengyuan Ye, Bei Ouyang, Tianyi Qian +6
Large language models (LLMs) have unlocked a plethora of powerful applications at the network edge, such as intelligent personal assistants. Data privacy and security concerns have…
Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence
Liekang Zeng, Shengyuan Ye, Xu Chen +6
Recent years have witnessed a thriving growth of computing facilities connected at the network edge, cultivating edge networks as a fundamental infrastructure for supporting miscel…
Galaxy: A Resource-Efficient Collaborative Edge AI System for In-situ Transformer Inference
Shengyuan Ye, Jiangsu Du, Liekang Zeng +4
Transformer-based models have unlocked a plethora of powerful intelligent applications at the edge, such as voice assistant in smart home. Traditional deployment approaches offload…
Implementation of Big AI Models for Wireless Networks with Collaborative Edge Computing
Liekang Zeng, Shengyuan Ye, Xu Chen +1
Big Artificial Intelligence (AI) models have emerged as a crucial element in various intelligent applications at the edge, such as voice assistants in smart homes and autonomous ro…