A vision-language model outputs dual heatmaps for navigation affordance and facing to ground semantic instructions into executable free space, achieving higher affordance rates than waypoint regression across simulated robot embodiments.
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GLM-5V-Turbo integrates multimodal perception as a core part of reasoning and execution for agentic tasks, reporting strong results in visual tool use and multimodal coding while keeping text-only performance competitive.
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Beyond Waypoints: Dual-Heatmap Grounding for Cross-Embodiment Semantic Navigation
A vision-language model outputs dual heatmaps for navigation affordance and facing to ground semantic instructions into executable free space, achieving higher affordance rates than waypoint regression across simulated robot embodiments.
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GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
GLM-5V-Turbo integrates multimodal perception as a core part of reasoning and execution for agentic tasks, reporting strong results in visual tool use and multimodal coding while keeping text-only performance competitive.