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Wrapping prompts can make harmful attacks appear safer, increasing successful jailbreaks while undermining the reliability of internal safety scores.
TC-MAF achieves unprecedented anomaly detection performance by effectively fusing RGB and 3D evidence, setting a new benchmark in multimodal industrial applications.
Generating realistic, safety-critical maritime scenarios at scale is now possible by combining generative trajectory modeling with automated encounter pairing, moving beyond limited historical data or handcrafted templates.
Achieve 98% accuracy in maritime scene recognition by fusing image data, text descriptions, and MLLM outputs, then compress the model to 68MB with minimal performance loss.
