Yuan Wu

Dual Adversarial Co-Learning for Multi-Domain Text Classification

2019 · arXiv (Cornell University)

In this paper we propose a novel dual adversarial co-learning approach for multi-domain text classification (MDTC). The approach learns shared-private networks for feature extraction and deploys dual adversarial regularizations to align features across different domains …

Compression Meets Security: Low-Complexity Linear Collaborative Federated Learning With Enhanced Accuracy

2025 · IEEE Transactions on Mobile Computing

Federated learning (FL) has been regarded as a promising paradigm for enabling distributed model training over resource-limited edge devices. Although FL maintains data locality and enhances model generalization, it faces challenges such as model leakage …

A Survey on Evaluation of Large Language Models

2024 · ACM Transactions on Intelligent Systems and Technology

Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, …