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Hy-Embodied-VLM-1.0 outperforms its predecessor by 8.4% while activating only a fraction of the parameters, redefining efficiency in embodied agents.
Achieving $O(W)$ storage efficiency and high cache hit rates in a large-scale LLM serving system could redefine performance benchmarks for hybrid architectures in production.
SearchEyes achieves state-of-the-art performance in multimodal search by unifying training data, environments, and rewards into a cohesive simulated world.
Pruning 77.8% of visual tokens without losing performance could revolutionize the efficiency of multimodal large language models.
Cold items can be effectively denoised using content similarity, leading to substantial performance boosts in recommendation systems.
Envision4D transforms future scene extrapolation in autonomous driving, achieving unprecedented accuracy and stability in dynamic environments.
FlashTTS slashes First-Packet Latency to 325ms, revolutionizing real-time speech dialogue systems without sacrificing voice quality.
