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VCN-Bench is introduced, a VCN-Bench benchmark for probing closed-loop spatial reasoning over prior visual experience in MLLMs, and MV-DualVLN is proposed, a planning-oriented baseline that jointly leverages prior video and in-episode observations.
It is demonstrated that strengthening the understanding capability of the Boogu-Image system, through a stronger multimodal encoder, agentic prompt rewriting, and related techniques, together with improvements in data quality, training pipelines, and agentic inference-time scaling, can substantially enhance generation...
The Geometry Grounded Tracking Anything Model is proposed, a unified framework for promptable instance tracking in 3D using only unordered RGB images or videos and delivers strong cross-view consistency, promptable instance spatial tracking, video object segmentation and spatial reconstruction, establishing a foundatio...
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