activity
20242026
collaborators

7 papers

cs.CV2026

Decoupling Vision and Language: Codebook Anchored Visual Adaptation

Jason Wu, Tianchen Zhao, Chang Liu +7

Large Vision-Language Models (LVLMs) use their vision encoders to translate images into representations for downstream reasoning, but the encoders often underperform in domain-spec…

cs.LG2025

ADMN: A Layer-Wise Adaptive Multimodal Network for Dynamic Input Noise and Compute Resources

Jason Wu, Yuyang Yuan, Kang Yang +2

Multimodal deep learning systems are deployed in dynamic scenarios due to the robustness afforded by multiple sensing modalities. Nevertheless, they struggle with varying compute r…

cs.AI2025

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…

eess.SP2025

MobiVital: Self-supervised Time-series Quality Estimation for Contactless Respiration Monitoring Using UWB Radar

Ziqi Wang, Derek Hua, Wenjun Jiang +3

Respiration waveforms are increasingly recognized as important biomarkers, offering insights beyond simple respiration rates, such as detecting breathing irregularities for disease…

cs.LG2025

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…

cs.CV2024

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…