Search Results for author: Yuanchun Li

Found 17 papers, 8 papers with code

Exploring the Impact of In-Browser Deep Learning Inference on Quality of User Experience and Performance

no code implementations8 Feb 2024 QiPeng Wang, Shiqi Jiang, Zhenpeng Chen, Xu Cao, Yuanchun Li, Aoyu Li, Ying Zhang, Yun Ma, Ting Cao, Xuanzhe Liu

Additionally, we noticed that in-browser inference increases the time it takes for graphical user interface (GUI) components to load in web browsers by a significant 67. 2\%, which severely impacts the overall QoE for users of web applications that depend on this technology.

A Survey of Resource-efficient LLM and Multimodal Foundation Models

1 code implementation16 Jan 2024 Mengwei Xu, Wangsong Yin, Dongqi Cai, Rongjie Yi, Daliang Xu, QiPeng Wang, Bingyang Wu, Yihao Zhao, Chen Yang, Shihe Wang, Qiyang Zhang, Zhenyan Lu, Li Zhang, Shangguang Wang, Yuanchun Li, Yunxin Liu, Xin Jin, Xuanzhe Liu

Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment.

Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

1 code implementation10 Jan 2024 Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, Rui Kong, Yile Wang, Hanfei Geng, Jian Luan, Xuefeng Jin, Zilong Ye, Guanjing Xiong, Fan Zhang, Xiang Li, Mengwei Xu, Zhijun Li, Peng Li, Yang Liu, Ya-Qin Zhang, Yunxin Liu

Next, we discuss several key challenges to achieve intelligent, efficient and secure Personal LLM Agents, followed by a comprehensive survey of representative solutions to address these challenges.

Accelerating In-Browser Deep Learning Inference on Diverse Edge Clients through Just-in-Time Kernel Optimizations

no code implementations16 Sep 2023 Fucheng Jia, Shiqi Jiang, Ting Cao, Wei Cui, Tianrui Xia, Xu Cao, Yuanchun Li, Deyu Zhang, Ju Ren, Yunxin Liu, Lili Qiu, Mao Yang

Web applications are increasingly becoming the primary platform for AI service delivery, making in-browser deep learning (DL) inference more prominent.

Empowering LLM to use Smartphone for Intelligent Task Automation

no code implementations29 Aug 2023 Hao Wen, Yuanchun Li, Guohong Liu, Shanhui Zhao, Tao Yu, Toby Jia-Jun Li, Shiqi Jiang, Yunhao Liu, Yaqin Zhang, Yunxin Liu

Mobile task automation is an attractive technique that aims to enable voice-based hands-free user interaction with smartphones.

Language Modelling

Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints

no code implementations29 Aug 2023 Wenxing Xu, Yuanchun Li, Jiacheng Liu, Yi Sun, Zhengyang Cao, Yixuan Li, Hao Wen, Yunxin Liu

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 environments.

Image Classification object-detection +1

SwapMoE: Efficient Memory-Constrained Serving of Large Sparse MoE Models via Dynamic Expert Pruning and Swapping

no code implementations29 Aug 2023 Rui Kong, Yuanchun Li, Qingtian Feng, Weijun Wang, Linghe Kong, Yunxin Liu

The main idea of SwapMoE is to keep a small dynamic set of important experts, namely Virtual Experts, in the main memory for inference, while seamlessly maintaining how the Virtual Experts map to the actual experts.

object-detection Object Detection

PatchBackdoor: Backdoor Attack against Deep Neural Networks without Model Modification

1 code implementation22 Aug 2023 Yizhen Yuan, Rui Kong, Shenghao Xie, Yuanchun Li, Yunxin Liu

However, most backdoor attacks have to modify the neural network models through training with poisoned data and/or direct model editing, which leads to a common but false belief that backdoor attack can be easily avoided by properly protecting the model.

Backdoor Attack Model Editing

DroidBot-GPT: GPT-powered UI Automation for Android

no code implementations14 Apr 2023 Hao Wen, Hongming Wang, Jiaxuan Liu, Yuanchun Li

Given a natural language description of a desired task, DroidBot-GPT can automatically generate and execute actions that navigate the app to complete the task.


AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments

no code implementations13 Mar 2023 Hao Wen, Yuanchun Li, Zunshuai Zhang, Shiqi Jiang, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, Yunxin Liu

Model elastification generates a high-quality search space of model architectures with the guidance of a developer-specified oracle model.


FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients

1 code implementation5 Jan 2022 Jaemin Shin, Yuanchun Li, Yunxin Liu, Sung-Ju Lee

Federated Learning (FL) trains a machine learning model on distributed clients without exposing individual data.

Federated Learning

PatchCensor: Patch Robustness Certification for Transformers via Exhaustive Testing

no code implementations19 Nov 2021 Yuheng Huang, Lei Ma, Yuanchun Li

Vision Transformer (ViT) is known to be highly nonlinear like other classical neural networks and could be easily fooled by both natural and adversarial patch perturbations.

DistFL: Distribution-aware Federated Learning for Mobile Scenarios

1 code implementation22 Oct 2021 Bingyan Liu, Yifeng Cai, Ziqi Zhang, Yuanchun Li, Leye Wang, Ding Li, Yao Guo, Xiangqun Chen

Previous studies focus on the "symptoms" directly, as they try to improve the accuracy or detect possible attacks by adding extra steps to conventional FL models.

Federated Learning Privacy Preserving

Representational Continuity for Unsupervised Continual Learning

2 code implementations ICLR 2022 Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang

Continual learning (CL) aims to learn a sequence of tasks without forgetting the previously acquired knowledge.

Continual Learning

ModelDiff: Testing-Based DNN Similarity Comparison for Model Reuse Detection

1 code implementation11 Jun 2021 Yuanchun Li, Ziqi Zhang, Bingyan Liu, Ziyue Yang, Yunxin Liu

The knowledge of a deep learning model may be transferred to a student model, leading to intellectual property infringement or vulnerability propagation.

Model Compression Transfer Learning

DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection

no code implementations18 Jan 2021 Yuanchun Li, Jiayi Hua, Haoyu Wang, Chunyang Chen, Yunxin Liu

The core of the attack is a neural conditional branch constructed with a trigger detector and several operators and injected into the victim model as a malicious payload.

Backdoor Attack

Beyond the Virus: A First Look at Coronavirus-themed Mobile Malware

1 code implementation29 May 2020 Ren He, Haoyu Wang, Pengcheng Xia, Liu Wang, Yuanchun Li, Lei Wu, Yajin Zhou, Xiapu Luo, Yao Guo, Guoai Xu

To facilitate future research, we have publicly released all the well-labelled COVID-19 themed apps (and malware) to the research community.

Cryptography and Security

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