1 citations · 1 across the 8 of their papers we have counts for
8 papers
MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction
Junbo Cui, Bokai Xu, Chongyi Wang +33
Recent progress in multimodal large language models (MLLMs) has brought AI capabilities from static offline data processing to real-time streaming interaction, yet they still remai…
Generative AI Meets Wireless Sensing: Towards Wireless Foundation Model
Zheng Yang, Guoxuan Chi, Chenshu Wu +5
Generative Artificial Intelligence (GenAI) has made significant advancements in fields such as computer vision (CV) and natural language processing (NLP), demonstrating its capabil…
MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe
Tianyu Yu, Zefan Wang, Chongyi Wang +31
Multimodal Large Language Models (MLLMs) are undergoing rapid progress and represent the frontier of AI development. However, their training and inference efficiency have emerged a…
Confidence-driven Gradient Modulation for Multimodal Human Activity Recognition: A Dynamic Contrastive Dual-Path Learning Approach
Panpan Ji, Junni Song, Yifan Lu +3
Sensor-based Human Activity Recognition (HAR) is a core technology that enables intelligent systems to perceive and interact with their environment. However, multimodal HAR systems…
USAD: End-to-End Human Activity Recognition via Diffusion Model with Spatiotemporal Attention
Hang Xiao, Ying Yu, Jiarui Li +4
The primary objective of human activity recognition (HAR) is to infer ongoing human actions from sensor data, a task that finds broad applications in health monitoring, safety prot…
Process Optimization and Deployment for Sensor-Based Human Activity Recognition Based on Deep Learning
Hanyu Liu, Ying Yu, Hang Xiao +4
Sensor-based human activity recognition is a key technology for many human-centered intelligent applications. However, this research is still in its infancy and faces many unresolv…
Redundant feature screening method for human activity recognition based on attention purification mechanism
Xiaoyang Li, Yixuan Jiang, Junze Zhu +4
In the field of sensor-based Human Activity Recognition (HAR), deep neural networks provide advanced technical support. Many studies have proven that recognition accuracy can be im…
CMD-HAR: Cross-Modal Disentanglement for Wearable Human Activity Recognition
Ying Yu, Siyao Li, Yixuan Jiang +5
Human Activity Recognition (HAR) is a fundamental technology for numerous human - centered intelligent applications. Although deep learning methods have been utilized to accelerate…