3 citations · 5 across the 12 of their papers we have counts for
12 papers
MobileExplorer: Accelerating On-Device Inference for Mobile GUI Agents via Online Exploration
Runxi Huang, Liyu Zhang, Shengzhong Liu +1
Mobile graphical user interface (GUI) agents enable AI models to autonomously operate smartphones on behalf of users. However, most existing systems focus primarily on optimizing t…
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signals
Tomoyoshi Kimura, Denizhan Kara, Jinyang Li +6
Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to support intelligent applications such as human activity analysis, emo…
PowerLens: Taming LLM Agents for Safe and Personalized Mobile Power Management
Xingyu Feng, Chang Sun, Yuzhu Wang +5
Battery life remains a critical challenge for mobile devices, yet existing power management mechanisms rely on static rules or coarse-grained heuristics that ignore user activities…
Can Time-Series Foundation Models Perform Building Energy Management Tasks?
Ozan Baris Mulayim, Pengrui Quan, Liying Han +4
Building energy management (BEM) tasks require processing and learning from a variety of time-series data. Existing solutions rely on bespoke task- and data-specific models to perf…
Toward Foundation Models for Online Complex Event Detection in CPS-IoT: A Case Study
Liying Han, Gaofeng Dong, Xiaomin Ouyang +3
Complex events (CEs) play a crucial role in CPS-IoT applications, enabling high-level decision-making in domains such as smart monitoring and autonomous systems. However, most exis…
InfoMAE: Pair-Efficient Cross-Modal Alignment for Multimodal Time-Series Sensing Signals
Tomoyoshi Kimura, Xinlin Li, Osama Hanna +10
Standard multimodal self-supervised learning (SSL) algorithms regard cross-modal synchronization as implicit supervisory labels during pretraining, thus posing high requirements on…
Scaling Online Complex Event Detection with Synthetic Supervision and Mamba-Based Neural Algorithmic Reasoning
Liying Han, Gaofeng Dong, Xiaomin Ouyang +4
Modern machine learning models excel at detecting individual actions, sounds, or scene attributes from short, localized observations. However, many real-world tasks, such as in sma…
MMBind: Unleashing the Potential of Distributed and Heterogeneous Data for Multimodal Learning in IoT
Xiaomin Ouyang, Jason Wu, Tomoyoshi Kimura +4
Multimodal sensing systems are increasingly prevalent in various real-world applications. Most existing multimodal learning approaches heavily rely on training with a large amount…
SensorBench: Benchmarking LLMs in Coding-Based Sensor Processing
Pengrui Quan, Xiaomin Ouyang, Jeya Vikranth Jeyakumar +3
Effective processing, interpretation, and management of sensor data have emerged as a critical component of cyber-physical systems. Traditionally, processing sensor data requires p…
FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors
Jason Wu, Ziqi Wang, Xiaomin Ouyang +5
Localization is a critical technology for various applications ranging from navigation and surveillance to assisted living. Localization systems typically fuse information from sen…
LLMSense: Harnessing LLMs for High-level Reasoning Over Spatiotemporal Sensor Traces
Xiaomin Ouyang, Mani Srivastava
Most studies on machine learning in sensing systems focus on low-level perception tasks that process raw sensory data within a short time window. However, many practical applicatio…
FedKit: Enabling Cross-Platform Federated Learning for Android and iOS
Sichang He, Beilong Tang, Boyan Zhang +4
We present FedKit, a federated learning (FL) system tailored for cross-platform FL research on Android and iOS devices. FedKit pipelines cross-platform FL development by enabling m…