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Achieving parallel region captioning with multimodal diffusion models could revolutionize the efficiency of visual perception tasks.
MFD reduces noise and boosts stability in flow matching models, achieving state-of-the-art results in challenging generative tasks.
Ditch the textual explanations: symbolic outputs like bounding boxes are the secret sauce for boosting multimodal verifier performance.
Forget finetuning on curated datasets – OpenClaw-RL lets agents learn directly and continuously from *every* interaction, turning user replies, tool outputs, and even GUI changes into valuable RL signals.
