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Explicitly learning spatial priorities boosts infrared target detection performance, achieving up to 89.00 F1 score with real-gaze supervision.
ACT revolutionizes skeletal animation by achieving unprecedented fidelity and temporal consistency through innovative trajectory conditioning.
Achieving up to 65% energy savings on mobile devices without sacrificing quality of experience could redefine on-device LLM deployment.
Omni-MLLMs often underperform unimodal models due to flawed fusion architectures, but a new "Chain of Modality" approach dynamically orchestrates input modalities to fix this.
Forget prompt engineering – ClawLess offers formally verified security policies for AI agents, even when they're trying to break the rules.
