Showing 2026Show all
2 papers · 1 filter
cs.CV2026
Adaptive Debiasing Tsallis Entropy for Test-Time Adaptation
Xiangyu Wu, Dongming Jiang, Feng Yu +5
Mainstream Test-Time Adaptation (TTA) methods for adapting vision-language models, e.g., CLIP, typically rely on Shannon Entropy (SE) at test time to measure prediction uncertainty…
cs.CR2026
Safe-FedLLM: Delving into the Safety of Federated Large Language Models
Mingxiang Tao, Yu Tian, Wenxuan Tu +3
Federated learning (FL) addresses privacy and data-silo issues in the training of large language models (LLMs). Most prior work focuses on improving the efficiency of federated lea…