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FedLNS effectively screens out malicious updates in federated learning, achieving superior model performance without compromising client privacy.
Reducing video transmission latency by targeting pixel-correlated areas can transform UAV vision systems, enhancing real-time operator assistance.
Visual observations can be transformed into editable city layouts with a surprising level of detail and accuracy using a multimodal large language model.
CookVoice achieves high-quality, style-controllable voice generation with a fraction of the parameters, outperforming larger models in efficiency and flexibility.
Hierarchical referencing in video compression can lead to over 50% gains in perceptual quality metrics, revolutionizing generative reconstruction.
A multi-agent forensic reasoning framework outperforms leading closed-source models in deepfake detection by leveraging diverse analytical perspectives on forgery cues.
Hard prompt compressors can leave critical context gaps, leading to a staggering 60% of examples suffering from referential dangling, which severely impacts accuracy in multi-hop question answering.
