PROWBench: Do Video Models Render What the Program Specifies?

arXiv:2610.02205 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-05

Code: https://github.com/AlayaLab/PROWBench

Project page: https://alaya-lab.github.io/PROWBench

Terminology

• World Model — 42× in this paper · explained in 7 episodes
• Alignment — 38× in this paper · explained in 1 episode
• Consistency — 30× in this paper · explained in 3 episodes
• Benchmark — 27× in this paper · explained in 2 episodes
• Logic-Render Alignment — 22× in this paper
• Interaction Success Rate — 8× in this paper
• Conference on Computer Vision and Pattern Recognition — 7× in this paper
• Fidelity — 7× in this paper · explained in 2 episodes
• Actor — 6× in this paper · explained in 3 episodes
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Benchmarking — 4× in this paper · explained in 3 episodes
• Diffusion Models — 4× in this paper · explained in 6 episodes
• Foundation Models — 4× in this paper · explained in 7 episodes
• CVF International Conference on Computer Vision — 3× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Provenance — 3× in this paper · explained in 3 episodes
• Temporal consistency — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Closed-Loop Control — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Optical Flow — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• World Simulation with Video Foundation Models for Physical AI
• MemoBench: Benchmarking World Modeling in Dynamically Changing Environments
• Code World Model: Coding Agent as World Brain
• PlayWorld: Benchmarking World Models with Agent Players over Long-Horizon Objectives
• Coarse-to-Real: Generative Rendering for Populated Dynamic Scenes
• ViPE: Video Pose Engine for 3D Geometric Perception
• Generative World Renderer
• Generative World Renderer at the Speed of Play
• Advancing Open-source World Models
• WorldPlay: Towards Long-Term Geometric Consistency for Real-Time Interactive World Modeling
• AlayaWorld: Interactive Long-Horizon World Modeling -- Full Technical Report
• Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory
• Omni-WorldBench: Towards a Comprehensive Interaction-Centric Evaluation for World Models
• WorldMark: A Unified Benchmark Suite for Interactive Video World Models
• MIND: Benchmarking Memory Consistency and Action Control in World Models
• WBench: A Comprehensive Multi-turn Benchmark for Interactive Video World Model Evaluation
• Matrix-Game: Interactive World Foundation Model
• CamI2V: Camera-Controlled Image-to-Video Diffusion Model

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