10 citations · 10 across the 6 of their papers we have counts for
6 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…
Neighborhood and Global Perturbations Supported SAM in Federated Learning: From Local Tweaks To Global Awareness
Boyuan Li, Zihao Peng, Yafei Li +4
Federated Learning (FL) can be coordinated under the orchestration of a central server to collaboratively build a privacy-preserving model without the need for data exchange. Howev…