InsightMap: Structured Spatial Modeling for Embodied Multimodal Reasoning

arXiv:2609.37187 · cs.CV, cs.RO · Submitted 2026-09-29 · Read on arXiv

cs.CV, cs.RO

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Grounding — 25× in this paper · explained in 3 episodes
• Visual Grounding — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Transformer — 5× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 2× in this paper
• Decode — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Vision-language models — 2× in this paper · explained in 2 episodes
• World Model — 2× in this paper · explained in 7 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Embeddings — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Multimodal Learning — 1× in this paper · explained in 2 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Regret — 1× in this paper · explained in 3 episodes
• ScanRefer for Visual Grounding — 1× in this paper
• Trace — 1× in this paper · explained in 2 episodes

Sources

• ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments
• GridMM: Grid Memory Map for Vision-and-Language Navigation
• Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation
• MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation
• Cosmos World Foundation Model Platform for Physical AI
• World Action Models are Zero-shot Policies
• Emerging Properties in Unified Multimodal Pretraining
• NaVid: Video-based VLM Plans the Next Step for Vision-and-Language Navigation
• NaVILA: Legged Robot Vision-Language-Action Model for Navigation
• InstructNav: Zero-shot System for Generic Instruction Navigation in Unexplored Environment
• BEVBert: Multimodal Map Pre-training for Language-guided Navigation
• Lookahead Exploration with Neural Radiance Representation for Continuous Vision-Language Navigation
• ScanQA: 3D Question Answering for Spatial Scene Understanding
• SQA3D: Situated Question Answering in 3D Scenes
• ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
• 3D-LLM: Injecting the 3D World into Large Language Models
• Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers
• 3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer
• Video-3D LLM: Learning Position-Aware Video Representation for 3D Scene Understanding
• GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Models

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