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A novel interactive agent outperforms traditional LLMs by transforming vague candidate requests into precise sourcing outcomes, achieving unmatched relevance and coverage.
TIGA can generate high-quality, detector-evasive images on-the-fly, bypassing the need for source images or model retraining, which could revolutionize evasion strategies against AIGC detectors.
Forget axis-aligned biases: TopoMamba's topology-aware scanning and HSIC-gated fusion unlocks more accurate medical image segmentation, especially for tricky curved structures.
Forget pixel-level noise: FogFool shows that physically-plausible, atmospherically-modeled fog can achieve 84% transfer attack success rate against remote sensing image classifiers, even surviving JPEG compression.
