1 citations · 2 across the 13 of their papers we have counts for
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APFL: Analytic Personalized Federated Learning via Dual-Stream Least Squares
Kejia Fan, Jianheng Tang, Zhirui Yang +8
Personalized Federated Learning (PFL) has presented a significant challenge to deliver personalized models to individual clients through collaborative training. Existing PFL method…
FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions
Jianheng Tang, Zhirui Yang, Jingchao Wang +7
Lately, Personalized Federated Learning (PFL) has emerged as a prevalent paradigm to deliver personalized models by collaboratively training while simultaneously adapting to each c…
AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
Jianheng Tang, Huiping Zhuang, Jingyu He +10
Federated Continual Learning (FCL) enables distributed clients to collaboratively train a global model from online task streams in dynamic real-world scenarios. However, existing F…
Towards Efficient and Exact Forgetting Services in Pre-Trained-Model-based Continual Learning
Yajiang Huang, Jianheng Tang, Kejia Fan +6
In Continual Learning (CL), using a Pre-Trained Model (PTM) as the feature extractor has become a popular practice. Accompanied by analytic classifiers, the PTM-based methods have…
ZeroTuning: Unlocking the Initial Token's Power to Enhance Large Language Models Without Training
Feijiang Han, Xiaodong Yu, Jianheng Tang +3
Token-level attention tuning, a class of training-free methods including Post-hoc Attention Steering (PASTA) and Attention Calibration (ACT), has emerged as a promising approach fo…
Can LLMs Handle WebShell Detection? Overcoming Detection Challenges with Behavioral Function-Aware Framework
Feijiang Han, Jiaming Zhang, Chuyi Deng +2
WebShell attacks - where adversaries implant malicious scripts on web servers - remain a persistent threat. Prior machine-learning and deep-learning detectors typically depend on t…