5 papers
MemoVAD: Resource-Efficient Video Anomaly Detection via Dynamic Semantic Memory in Edge Computing Scenarios
Guo Li, Jiandian Zeng, Yang Li +3
Deploying Video Anomaly Detection (VAD) in real-world surveillance faces a fundamental tension between the demand for high-level semantics to ensure effectiveness and the limited c…
HiLoRA: Hierarchical Low-Rank Adaptation for Personalized Federated Learning
Zihao Peng, Nan Zou, Jiandian Zeng +4
Vision Transformers (ViTs) have been widely adopted in vision tasks due to their strong transferability. In Federated Learning (FL), where full fine-tuning is communication heavy,…
Matrix as Plan: Structured Logical Reasoning with Feedback-Driven Replanning
Ke Chen, Jiandian Zeng, Zihao Peng +3
As knowledge and semantics on the web grow increasingly complex, enhancing Large Language Models (LLMs)' comprehension and reasoning capabilities has become particularly important.…
FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation
Zihao Peng, Jiandian Zeng, Boyuan Li +3
Federated Learning (FL) facilitates the fine-tuning of Foundation Models (FMs) using distributed data sources, with Low-Rank Adaptation (LoRA) gaining popularity due to its low com…
Federated Learning for Diffusion Models
Zihao Peng, Xijun Wang, Shengbo Chen +2
Diffusion models are powerful generative models that can produce highly realistic samples for various tasks. Typically, these models are constructed using centralized, independentl…