Training Object Permanence in World Models

arXiv:2609.28654 · cs.AI, cs.CV · Submitted 2026-09-23 · Read on arXiv

cs.AI, cs.CV

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Object Permanence — 48× in this paper
• World Model — 37× in this paper · explained in 7 episodes
• Core — 19× in this paper · explained in 2 episodes
• Benchmark — 16× in this paper · explained in 2 episodes
• Aperture — 10× in this paper · explained in 1 episode
• Object Solidity — 7× in this paper
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Foundation Model — 3× in this paper · explained in 3 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• World Reasoning with Object Permanence — 3× in this paper
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• APEX — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Causal Reasoning — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Momentum transfer — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes

Sources

• MMGR: Multi-Modal Generative Reasoning Benchmark and Evaluation
• Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark
• LTX-2: Efficient Joint Audio-Visual Foundation Model
• RULER-Bench: Probing Rule-based Reasoning Abilities of Next-level Video Generation Models for Vision Foundation Intelligence
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• Core Knowledge Deficits in Multi-Modal Language Models
• Can World Simulators Reason? Gen-ViRe: A Generative Visual Reasoning Benchmark
• The Philosophical Foundations of Growing AI Like A Child
• Increasing Computation Resolves Conflicts in Vision Language Models
• Cosmos 3: Omnimodal World Models for Physical AI
• Cosmos World Foundation Model Platform for Physical AI
• Movie Gen: A Cast of Media Foundation Models
• Probing Perceptual Constancy in Large Vision-Language Models
• Wan: Open and Advanced Large-Scale Video Generative Models
• Video models are zero-shot learners and reasoners
• VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning
• Reasoning via Video: The First Evaluation of Video Models' Reasoning Abilities through Maze-Solving Tasks
• CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

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