4 papers
CoE: Collaborative Entropy for Uncertainty Quantification in Agentic Multi-LLM Systems
Kangkang Sun, Jun Wu, Jianhua Li +3
Uncertainty estimation in multi-LLM systems remains largely single-model-centric: existing methods quantify uncertainty within each model but do not adequately capture semantic dis…
Privacy as Commodity: MFG-RegretNet for Large-Scale Privacy Trading in Federated Learning
Kangkang Sun, Jianhua Li, Xiuzhen Chen +2
Federated Learning (FL) has emerged as a prominent paradigm for privacy-preserving distributed machine learning, yet two fundamental challenges hinder its large-scale adoption. Fir…
FedPF: Accurate Target Privacy Preserving Federated Learning Balancing Fairness and Utility
Kangkang Sun, Jun Wu, Minyi Guo +2
Federated Learning (FL) enables collaborative model training without data sharing, yet participants face a fundamental challenge, e.g., simultaneously ensuring fairness across demo…
Model-Agnostic Sentiment Distribution Stability Analysis for Robust LLM-Generated Texts Detection
Siyuan Li, Xi Lin, Guangyan Li +5
The rapid advancement of large language models (LLMs) has resulted in increasingly sophisticated AI-generated content, posing significant challenges in distinguishing LLM-generated…