activity
20242026
collaborators

5 papers

cs.CR2026

MANA: Towards Efficient Mobile Ad Detection via Multimodal Agentic UI Navigation

Yizhe Zhao, Yongjian Fu, Zihao Feng +4

Mobile advertising dominates app monetization but introduces risks ranging from intrusive user experience to malware delivery. Existing detection methods rely either on static anal…

cs.LG2025

Gains: Fine-grained Federated Domain Adaptation in Open Set

Zhengyi Zhong, Wenzheng Jiang, Weidong Bao +5

Conventional federated learning (FL) assumes a closed world with a fixed total number of clients. In contrast, new clients continuously join the FL process in real-world scenarios,…

cs.CR2025

CSVAR: Enhancing Visual Privacy in Federated Learning via Adaptive Shuffling Against Overfitting

Zhuo Chen, Zhenya Ma, Yan Zhang +8

Although federated learning preserves training data within local privacy domains, the aggregated model parameters may still reveal private characteristics. This vulnerability stems…

cs.LG2025

ConCISE: Confidence-guided Compression in Step-by-step Efficient Reasoning

Ziqing Qiao, Yongheng Deng, Jiali Zeng +7

Large Reasoning Models (LRMs) perform strongly in complex reasoning tasks via Chain-of-Thought (CoT) prompting, but often suffer from verbose outputs, increasing computational over…

cs.LG2025

AugFL: Augmenting Federated Learning with Pretrained Models

Sheng Yue, Zerui Qin, Yongheng Deng +3

Federated Learning (FL) has garnered widespread interest in recent years. However, owing to strict privacy policies or limited storage capacities of training participants such as I…