4 citations · 5 across the 14 of their papers we have counts for
4 papers · 1 filter
FedPix: Learning What to Share with Less Leakage in Federated Intelligence
Jingwei Zhao, Tiantong Sun, Yuanyuan Song +7
Existing federated intelligence paradigms primarily focus on how models are trained or aggregated, while overlooking a more fundamental question: \textbf{what information should le…
Lost in Implicit Routing: How LLM Agents Fail to Load Relevant Skills at Scale
Jinlin Liu, Wei Chen, Xiaojin Zhang
Reusable skills let LLM agents load task-specific instructions on demand, but they make execution depend on implicit routing over skill metadata. We test whether this design scales…
ViCrop-Det: Spatial Attention Entropy Guided Cropping for Training-Free Small-Object Detection
Hui Wang, Hongze Li, Wei Chen +1
Transformer-based architectures have established a dominant paradigm in global semantic perception; however, they remain fundamentally constrained by the profound spatial heterogen…
Perturbation-Induced Linearization: Constructing Unlearnable Data with Solely Linear Classifiers
Jinlin Liu, Wei Chen, Xiaojin Zhang
Collecting web data to train deep models has become increasingly common, raising concerns about unauthorized data usage. To mitigate this issue, unlearnable examples introduce impe…