G squared WAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation

cs.AI, cs.RO

Submitted: 2026-10-12

Updated: 2026-10-12

Comments: 20 pages, including references and appendix

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• NavWAM: A Navigation World Action Model for Goal-Conditioned Visual Navigation
• AnyImageNav: Any-View Geometry for Precise Last-Meter Image-Goal Navigation
• Drift-Resistant Navigation World Model with Anchored Epipolar Guidance
• LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
• DINOv3
• Latent Spatial Memory for Video World Models
• WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation
• Efficient Image-Goal Navigation with Representative Latent World Model

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