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ConfigWM introduces configurable perception for world models, using task descriptions to steer visual embeddings into task-specific state spaces that filter out irrelevant distractions, achieving 22.3% better planning success over the strongest baseline in noisy environments.
ScaleNav通过在互联网第一人称视频上预训练目标导向视觉动态，结合动作对齐与联合微调，实现语言条件下的局部导航，在仿真与真实四足机器人部署上取得高成功率并超越基线。
Proposes S2ST-Omni 2, a many-to-one compositional speech-to-speech translation framework that replaces flat language labels with structured typological priors to improve multilingual adaptation, achieving superior performance on CVSS-C.