An agentic VLM approach with dynamic cognitive maps and Spatial Assertion Codes reaches 80.5% accuracy on MindCube, gaining 29.5 points on rotation tasks via dense-reward RL.
Cov: Chain-of-view prompting for spatial reasoning
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Integrating generative novel-view synthesis into LMM reasoning loops improves accuracy on spatial subtasks by 1.3 to 3.9 percentage points across multiple models and tasks.
UniMesh unifies 3D mesh generation and understanding in one model via a Mesh Head interface, Chain of Mesh iterative editing, and an Actor-Evaluator self-reflection loop.
citing papers explorer
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Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
An agentic VLM approach with dynamic cognitive maps and Spatial Assertion Codes reaches 80.5% accuracy on MindCube, gaining 29.5 points on rotation tasks via dense-reward RL.
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Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence
Integrating generative novel-view synthesis into LMM reasoning loops improves accuracy on spatial subtasks by 1.3 to 3.9 percentage points across multiple models and tasks.
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UniMesh: Unifying 3D Mesh Understanding and Generation
UniMesh unifies 3D mesh generation and understanding in one model via a Mesh Head interface, Chain of Mesh iterative editing, and an Actor-Evaluator self-reflection loop.