collaborators

6 papers

cs.LG2025

Communication-Aware Knowledge Distillation for Federated LLM Fine-Tuning over Wireless Networks

Xinlu Zhang, Na Yan, Yang Su +2

Federated learning (FL) for large language models (LLMs) offers a privacy-preserving scheme, enabling clients to collaboratively fine-tune locally deployed LLMs or smaller language…

eess.SP2025

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…

cs.LG2025

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…

cs.LG2025

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…

q-bio.OT2025

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.…

cs.LG2025

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…