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cs.LG2026
Rethinking Factor Sharing in Federated LoRA: A Rank-Aware Adaptive Approach
Xinyi Xu, Bingnan Xiao, Shuang Qin +2
Low-rank adaptation (LoRA) represents large language model (LLM) updates with two compact matrix factors, i.e., and , providing an efficient way to fine-tune large models in…
cs.LG2026
FedVSSAM: Mitigating Flatness Incompatibility in Sharpness-Aware Federated Learning
Bingnan Xiao, Yuan Gao, Bingcong Li +3
Sharpness-aware minimization (SAM) is an effective method for improving the generalization of federated learning (FL) by steering local training toward flat minima. Under data hete…
cs.LG2026
Adaptive Test-Time Compute Allocation for Reasoning LLMs via Constrained Policy Optimization
Zhiyuan Zhai, Bingcong Li, Bingnan Xiao +2
Test-time compute scaling, the practice of spending extra computation during inference via repeated sampling, search, or extended reasoning, has become a powerful lever for improvi…