2 papers
cs.AI2026
Active Testing of Large Language Models via Approximate Neyman Allocation
Zeli Liu, Jiancheng Zhang, Cong Liu +1
Large language models (LLMs) require reliable evaluation from pre-training to test-time scaling, making evaluation a recurring rather than one-off cost. As model scales grow and ta…
cs.LG2025
FedPaI: Achieving Extreme Sparsity in Federated Learning via Pruning at Initialization
Haonan Wang, Zeli Liu, Kajimusugura Hoshino +3
Federated Learning (FL) enables distributed training on edge devices but faces significant challenges due to resource constraints in edge environments, impacting both communication…