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Xuanyu Chen

2 accepted papers

2026

Scaling Law Analysis in Federated Learning: How to Select the Optimal Model Size?

AAAI 2026technical

The recent success of large language models (LLMs) has sparked a growing interest in training large-scale models. As the model size continues to scale, concerns are growing about the depletion of high-quality, well-curated training data. This has led practitioners to explore training approaches like

Cited by 0SourcePDFScholar
2026

Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data

ICLR 2026poster

Recent research has introduced distributed self-supervised learning (D-SSL) approaches to leverage vast amounts of unlabeled decentralized data. However, D-SSL faces the critical challenge of data heterogeneity, and there is limited theoretical understanding of how different D-SSL frameworks respond…

Cited by 0SourceScholar