From Reasoning Failures to Composable Video Spatial Intelligence

arXiv:2610.01999 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• Benchmark — 26× in this paper · explained in 2 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Grounding — 10× in this paper · explained in 3 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Failure Taxonomy — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Agentic AI — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Qwen3-VL Technical Report
• Scaling Spatial Intelligence with Multimodal Foundation Models
• SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities
• SpaceTools: Tool-Augmented Spatial Reasoning via Double Interactive RL
• EgoMind: Activating Spatial Cognition through Linguistic Reasoning in MLLMs
• SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning
• S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence
• BLINK: Multimodal Large Language Models Can See but Not Perceive
• Map2Thought: Explicit 3D Spatial Reasoning via Metric Cognitive Maps
• Cog3DMap: Multi-View Vision-Language Reasoning with 3D Cognitive Maps
• FARM: Find Anything using Relational Spatial Memory
• Unleashing Spatial Reasoning in Multimodal Large Language Models via Textual Representation Guided Reasoning
• 3D-R1: Enhancing Reasoning in 3D VLMs for Unified Scene Understanding
• ViewSpatial-Bench: Evaluating Multi-perspective Spatial Localization in Vision-Language Models
• See&Trek: Training-Free Spatial Prompting for Multimodal Large Language Model
• VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning
• STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?
• From Hallucination to Grounding: Diagnosing Visual Spatial Intelligence via CRISP
• Improved Visual-Spatial Reasoning via R1-Zero-Like Training
• MMSI-Video-Bench: A Holistic Benchmark for Video-Based Spatial Intelligence

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