8 papers
Safety-aware Goal-oriented Semantic Sensing, Communication, and Control for Robotics
Wenchao Wu, Shutong Chen, Wenjie Liu +3
Wirelessly-connected robotic systems empower robots with real-time intelligence by leveraging remote computing resources for decision-making. However, the data exchange between rob…
Goal-Oriented Framework for Optical Flow-based Multi-User Multi-Task Video Transmission
Yujie Xu, Shutong Chen, Nan Li +3
Efficient multi-user multi-task video transmission is an important research topic within the realm of current wireless communication systems. To reduce the transmission burden and…
Molecule Mixture Detection and Design for MC Systems with Non-linear, Cross-reactive Receiver Arrays
Bastian Heinlein, Kaikai Zhu, Sümeyye Carkit-Yilmaz +6
Air-based molecular communication (MC) has the potential to be one of the first MC systems to be deployed in real-world applications, enabled by commercially available sensors. How…
Molecule Mixture Detection and Alphabet Design for Non-linear, Cross-reactive Receiver Arrays in MC
Bastian Heinlein, Kaikai Zhu, Sümeyye Carkit-Yilmaz +6
Air-based molecular communication (MC) has the potential to be one of the first MC systems to be deployed in real-world applications, enabled by existing sensor technologies such a…
PWC-MoE: Privacy-Aware Wireless Collaborative Mixture of Experts
Yang Su, Na Yan, Yansha Deng +1
Large language models (LLMs) hosted on cloud servers alleviate the computational and storage burdens on local devices but raise privacy concerns due to sensitive data transmission…
Modeling and Optimization of Insulin Injection for Type-1 Diabetes Mellitus Management
Rinrada Jadsadaphongphaibool, Dadi Bi, Christian D. Lorenz +2
Diabetes mellitus is a global health crisis characterized by poor blood sugar regulation, impacting millions of people worldwide and leading to severe complications and mortality.…
Federated Fine-Tuning of LLMs: Framework Comparison and Research Directions
Na Yan, Yang Su, Yansha Deng +1
Federated learning (FL) provides a privacy-preserving solution for fine-tuning pre-trained large language models (LLMs) using distributed private datasets, enabling task-specific a…
HAFLQ: Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization
Yang Su, Na Yan, Yansha Deng +2
Federated fine-tuning of pre-trained Large Language Models (LLMs) enables task-specific adaptation across diverse datasets while preserving privacy. However, challenges such as hig…