49 citations · 279 across the 48 of their papers we have counts for
7 papers · 1 filter
Empowering In-Browser Deep Learning Inference on Edge Devices with Just-in-Time Kernel Optimizations
Fucheng Jia, Shiqi Jiang, Ting Cao +9
Web is increasingly becoming the primary platform to deliver AI services onto edge devices, making in-browser deep learning (DL) inference more prominent. Nevertheless, the heterog…
Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints
Wenxing Xu, Yuanchun Li, Jiacheng Liu +5
Unlike cloud-based deep learning models that are often large and uniform, edge-deployed models usually demand customization for domain-specific tasks and resource-limited environme…
PatchBackdoor: Backdoor Attack against Deep Neural Networks without Model Modification
Yizhen Yuan, Rui Kong, Shenghao Xie +2
Backdoor attack is a major threat to deep learning systems in safety-critical scenarios, which aims to trigger misbehavior of neural network models under attacker-controlled condit…
AutoDroid: LLM-powered Task Automation in Android
Hao Wen, Yuanchun Li, Guohong Liu +7
Mobile task automation is an attractive technique that aims to enable voice-based hands-free user interaction with smartphones. However, existing approaches suffer from poor scalab…
SwapMoE: Serving Off-the-shelf MoE-based Large Language Models with Tunable Memory Budget
Rui Kong, Yuanchun Li, Qingtian Feng +5
Mixture of experts (MoE) is a popular technique to improve capacity of Large Language Models (LLMs) with conditionally-activated parallel experts. However, serving MoE models on me…
DroidBot-GPT: GPT-powered UI Automation for Android
Hao Wen, Hongming Wang, Jiaxuan Liu +1
This paper introduces DroidBot-GPT, a tool that utilizes GPT-like large language models (LLMs) to automate the interactions with Android mobile applications. Given a natural langua…
AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments
Hao Wen, Yuanchun Li, Zunshuai Zhang +5
Deep learning models are increasingly deployed to edge devices for real-time applications. To ensure stable service quality across diverse edge environments, it is highly desirable…