爱社交 发表于 2025-3-25 06:47:11
,DFADNet: A Diverse-Feature Adaptive Network for Web3.0-Oriented Deep Forgery Detection,d videos. DFADnet comprises three essential components: TextureNoiseAdapt (TNA) for adaptive extraction of texture noise; SemanticGuidance (SG) for directing focus towards semantic inconsistencies indicative of tampering; and TemporalMultiscale (TMS) for analyzing temporal dynamics across video framAnthology 发表于 2025-3-25 08:44:53
,Blockchain-Based Federated Recommendation with Incentive Mechanism, select optimal clients that can maximize the social surplus. Finally, we employ blockchain for on-chain evidence storage of models to ensure the safety of the federated recommendation system. The experimental results show that our proposed incentive mechanism can attract clients with superior train啜泣 发表于 2025-3-25 11:44:21
http://reply.papertrans.cn/20/1928/192733/192733_23.png揉杂 发表于 2025-3-25 16:34:51
http://reply.papertrans.cn/20/1928/192733/192733_24.png缺乏 发表于 2025-3-25 20:51:16
http://reply.papertrans.cn/20/1928/192733/192733_25.pngsuperfluous 发表于 2025-3-26 03:40:58
,Tailoring Noise to Fit: An Adaptive Noise Optimization Mechanism Against Gradient Leakage,transmitting model updates. However, the Gradient Leakage Attack (GLA) can reconstruct clients’ local data through transmitted gradients, posing a significant privacy threat to FL. Existing defense strategies against the GLA have the following limitations: (1) cryptography-based defenses impose highESO 发表于 2025-3-26 04:18:22
http://reply.papertrans.cn/20/1928/192733/192733_27.png偏见 发表于 2025-3-26 12:20:57
http://reply.papertrans.cn/20/1928/192733/192733_28.pngbrother 发表于 2025-3-26 15:31:31
,A Blockchain-Based Framework for Crowdsourcing Evaluation of Large Language Models,al human and material resources. This work proposes a crowdsourcing evaluation framework based on blockchain to comprehensively evaluate the toxicity of the outputs from LLMs. The framework offers LLM service to users and collects their evaluation scores for the outputs from the LLM. The evaluation跳动 发表于 2025-3-26 17:32:08
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