PoL-BFL is proposed, a framework that bridges a critical verification gap through a novel "verify-then-slash" paradigm to make verification economically decisive rather than exhaustive, and proves that honest participation is strictly more profitable than cheating for rational clients whenever the detection probability...
Xiubo Wei, Yahong Chen, Jiahui Hu et al.· Proceedings of the 32nd ACM...· 0 citations
Decentralized Federated Learning removes the need for a trusted central server but introduces a critical verification gap: participants cannot prove to each other that they have honestly executed the costly local training. This gap undermines both security and incentive alignment, as rational clients are tempted to che...
Xiubo Wei, Yahong Chen, Jiahui Hu et al.· Proceedings of the 32nd ACM...· 0 citations
Results show that privacy-sensitive visual and textual information can be recovered even from deep-layer LVLM hidden states, exposing the privacy risks of collaborative inference.
Shuaifan Jin, Zhibo Wang, Qiyuan Wang et al.· 0 citations
An attention-free and lightweight token reduction framework as a plug-and-play module for VLMs, which preserves both important and diverse tokens to produce a compact visual representation, and achieves a favorable accuracy-efficiency trade-off.
Xuanyi Hao, Zuoyuan Zhang, Zhibo Wang et al.· arXiv.org· 0 citations
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