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We present MOSS-VL, an open vision-language model family that treats real-time interaction -- perceiving while it speaks -- as a first-class capability. It is co-designed across the stack: the language decoder attends to vision only through gated cross-attention, so the model can naturally see incoming frames while gen...
OmniVAE is presented, a jointly trained audio-video VAE that learns fine-grained semantic alignment between audio and video latent representations that translates into higher generation quality and more accurate cross-modal synchronization in downstream text-to-audio-video generation.
HiMe is proposed, a Hierarchical Embodied Memory framework that decouples embodied intelligence into a high-frequency Executor for execution, a Sentry for working memory, and a Planner for long-term strategy, and introduces a dynamic knowledge system based on cross-modal semantic schemas and active management mechanism...
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