Resolving State-Representation Mismatch: State-Space Visual Reasoning for Open-Loop VLA Planning

arXiv:2609.33412 · cs.CV, cs.AI · Submitted 2026-09-27 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• KV cache — 10× in this paper · explained in 3 episodes
• Robustness — 9× in this paper · explained in 5 episodes
• Latent Space — 8× in this paper · explained in 7 episodes
• Decode — 7× in this paper · explained in 2 episodes
• State-Space Visual Reasoning — 5× in this paper
• Ablation — 4× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• Abstraction — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Exact Match — 2× in this paper
• Generalization — 2× in this paper · explained in 13 episodes
• Latent Visual Reasoning — 2× in this paper · explained in 2 episodes
• LoRA Adapters — 2× in this paper · explained in 3 episodes
• Multimodal Reasoning — 2× in this paper · explained in 5 episodes
• alpha — 2× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Decoupling — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Homogenization — 1× in this paper · explained in 2 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Progress Rate — 1× in this paper
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Vision-Language-Action (VLA) Models — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Flamingo: a Visual Language Model for Few-Shot Learning
• Qwen2.5-VL Technical Report
• Perception Tokens Enhance Visual Reasoning in Multimodal Language Models
• Thinking with Generated Images
• Retrieve, Integrate, and Synthesize: Spatial-Semantic Grounded Latent Visual Reasoning
• Simulation to Rules: A Dual-VLM Framework for Formal Visual Planning
• DeepEyesV2: Toward Agentic Multimodal Model
• A Configurable Library for Generating and Manipulating Maze Datasets
• ASCII Art Turns LLMs into VLA Controllers
• PureKV: Plug-and-Play KV Cache Optimization with Spatial-Temporal Sparse Attention for Vision-Language Large Models
• Mini-BEHAVIOR: A Procedurally Generated Benchmark for Long-horizon Decision-Making in Embodied AI
• Latent Visual Reasoning
• Imagine while Reasoning in Space: Multimodal Visualization-of-Thought
• Reasoning Within the Mind: Dynamic Multimodal Interleaving in Latent Space
• Thinking with Visual Abstract: Enhancing Multimodal Reasoning via Visual Abstraction
• Fill the GAP: A Granular Alignment Paradigm for Visual Reasoning in Multimodal Large Language Models
• How Visual Representations Map to Language Feature Space in Multimodal LLMs
• VLA-Thinker: Boosting Vision-Language-Action Models through Thinking-with-Image Reasoning
• Monet: Reasoning in Latent Visual Space Beyond Images and Language
• Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception

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