Vision-language navigation requires agents to follow natural-language instructions to reach target locations, making high-quality language supervision essential. Since human annotation is costly, prior work has explored scalable data synthesis methods. However, existing methods typically either use separate models for...
Song-Ze Li, Hao-Ming Gu, Zi-Yang Gong et al.· 0 citations
Language models trained with long-horizon agentic reinforcement learning can generalize knowledge through reasoning, express precise actions, and pursue goals over many steps, raising the ceiling on what an embodied agent can understand and decide. Physical interaction, however, remains the domain of action policies, w...
Geng-Ze Zhou, Yicong Hong, Jiazhao Zhang et al.· 0 citations
AnchorWeave is introduced, a memory-augmented video generation framework that replaces a single misaligned global memory with multiple clean local geometric memories and learns to reconcile their cross-view inconsistencies.
Zun Wang, Han Lin, Jaehong Yoon et al.· arXiv.org· 18 citations
V-Co, a systematic study of visual co-denoising in a unified JiT-based framework, outperforms the underlying pixel-space diffusion baseline and strong prior pixel-diffusion methods while using fewer training epochs, offering practical guidance for future representation-aligned generative models.
Han Lin, Xichen Pan, Zun Wang et al.· arXiv.org· 0 citations
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