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4 papers · 2 filters
HVAdam: A Full-Dimension Adaptive Optimizer
Yiheng Zhang, Shaowu Wu, Yuanzhuo Xu +4
Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However, they often generalize worse th…
Cross-Sample Augmented Test-Time Adaptation for Personalized Intraoperative Hypotension Prediction
Kanxue Li, Yibing Zhan, Hua Jin +3
Intraoperative hypotension (IOH) poses significant surgical risks, but accurate prediction remains challenging due to patient-specific variability. While test-time adaptation (TTA)…
RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference
Yaoqi Chen, Jinkai Zhang, Baotong Lu +16
Recent large language models (LLMs) are rapidly extending their context windows, yet inference throughput lags due to increasing GPU memory and bandwidth demands. This is because t…
Robust Asymmetric Heterogeneous Federated Learning with Corrupted Clients
Xiuwen Fang, Mang Ye, Bo Du
This paper studies a challenging robust federated learning task with model heterogeneous and data corrupted clients, where the clients have different local model structures. Data c…