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Malicious content can be injected into web agents' memories, achieving up to 99.15% attack success without affecting their benign performance.
Current image restoration models still fail to strike the right balance between noise reduction, detail fidelity, and accurate color in real-world, low-light portrait scenarios, highlighting a critical gap this challenge aims to close.
Current Chinese AI-generated text detection benchmarks are too homogeneous; C-ReD fixes this with real-world prompts and diverse LLMs, enabling better generalization.
By optimizing gradient inversions across hierarchical GAN feature spaces, GIFD achieves pixel-perfect reconstructions of private data in federated learning, even in challenging out-of-distribution scenarios.
Spatial awareness is the secret ingredient to unlocking better visual in-context learning, boosting performance across diverse vision tasks.
Achieve state-of-the-art long-horizon video understanding by compressing multimodal memories into high-level semantic schemas, enabling efficient reasoning without losing crucial details.
