31 citations · 31 across the 13 of their papers we have counts for
13 papers
AVI-Bench: Toward Human-like Audio-Visual Intelligence of Omni-MLLMs
Yaoting Wang, Ziyi Zhang, Wenming Tu +10
Recent advances in Omni-Multimodal Large Language Models (Omni-MLLMs) have enabled strong integration of vision, audio, and language. However, their audio-visual intelligence (AVI)…
Mobile GUI Agents under Real-world Threats: Are We There Yet?
Guohong Liu, Jialei Ye, Jiacheng Liu +5
Recent years have witnessed a rapid development of mobile GUI agents powered by large language models (LLMs), which can autonomously execute diverse device-control tasks based on n…
LLM-Explorer: Towards Efficient and Affordable LLM-based Exploration for Mobile Apps
Shanhui Zhao, Hao Wen, Wenjie Du +5
Large language models (LLMs) have opened new opportunities for automated mobile app exploration, an important and challenging problem that used to suffer from the difficulty of gen…
Mobile-Bench-v2: A More Realistic and Comprehensive Benchmark for VLM-based Mobile Agents
Weikai Xu, Zhizheng Jiang, Yuxuan Liu +7
VLM-based mobile agents are increasingly popular due to their capabilities to interact with smartphone GUIs and XML-structured texts and to complete daily tasks. However, existing…
KVShare: An LLM Service System with Efficient and Effective Multi-Tenant KV Cache Reuse
Huan Yang, Renji Zhang, Mingzhe Huang +5
Recent advances in long-text understanding have pushed the context length of large language models (LLMs) up to one million tokens. It boosts LLMs's accuracy and reasoning capacity…
Threshold Neuron: A Brain-inspired Artificial Neuron for Efficient On-device Inference
Zihao Zheng, Yuanchun Li, Jiayu Chen +3
Enhancing the computational efficiency of on-device Deep Neural Networks (DNNs) remains a significant challengein mobile and edge computing. As we aim to execute increasingly compl…
ChainStream: An LLM-based Framework for Unified Synthetic Sensing
Jiacheng Liu, Yuanchun Li, Liangyan Li +5
Many applications demand context sensing to offer personalized and timely services. Yet, developing sensing programs can be challenging for developers and using them is privacy-con…
AutoDroid-V2: Boosting SLM-based GUI Agents via Code Generation
Hao Wen, Shizuo Tian, Borislav Pavlov +8
Large language models (LLMs) have brought exciting new advances to mobile UI agents, a long-standing research field that aims to complete arbitrary natural language tasks through m…
A First Look At Efficient And Secure On-Device LLM Inference Against KV Leakage
Huan Yang, Deyu Zhang, Yudong Zhao +2
Running LLMs on end devices has garnered significant attention recently due to their advantages in privacy preservation. With the advent of lightweight LLM models and specially des…
Region-based Content Enhancement for Efficient Video Analytics at the Edge
Weijun Wang, Liang Mi, Shaowei Cen +4
Video analytics is widespread in various applications serving our society. Recent advances of content enhancement in video analytics offer significant benefits for the bandwidth sa…
LoRA-Switch: Boosting the Efficiency of Dynamic LLM Adapters via System-Algorithm Co-design
Rui Kong, Qiyang Li, Xinyu Fang +7
Recent literature has found that an effective method to customize or further improve large language models (LLMs) is to add dynamic adapters, such as low-rank adapters (LoRA) with…
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Yuanchun Li, Hao Wen, Weijun Wang +22
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have been one of the key technologies that researchers and engineers have focused on, aiming…
BiSwift: Bandwidth Orchestrator for Multi-Stream Video Analytics on Edge
Lin Sun, Weijun Wang, Tingting Yuan +4
High-definition (HD) cameras for surveillance and road traffic have experienced tremendous growth, demanding intensive computation resources for real-time analytics. Recently, offl…