Beyond Pixels: From Video Priors to 4D Worlds

arXiv 2026 22.6 method

TLDR

Introduces Latent-to-4D, a method for direct 4D scene generation from video diffusion latents, bypassing RGB and transferring across video generators within a VAE family.

Reasoning

The paper presents a novel latent-to-4D interface with strong empirical results on benchmarks and human evaluation, and demonstrates transfer across video generators. Weaknesses include reliance on a shared VAE family and limited training data, with potential generalization concerns not fully addressed in the abstract.

Read-first score

Read-first score 22.6, weighted from topical fit, citation, graph, method, reproducibility, and recency signals. Original total remains 12.

Recency 6%

100

Uses a gentle age decay so recent papers surface without erasing older foundations. 2026

Reproducibility 18%

Screens links and visible text for paper, code, dataset, artifact, and repository signals. pdf=True; code=False; dataset=False; markers=checkpoint,code

Methodology quality 18%

Screens visible abstract and analysis fields for experiment, dataset, baseline, metric, and limitation evidence. markers=none

Topical relevance 29%

17.1

Uses existing LLM keyword relevance scores normalized to 0-100. world model,world simulator,generative world model,interactive world model,video world model,world dynamics prediction,model-based reinforcement learning world model

Citation impact 18%

Uses OpenAlex-shaped citation metadata as a bibliometric attention signal, separate from paper quality. cited_by_count=0

Citation velocity 12%

Citation velocity estimates citations per publication-year to reduce old-paper bias. velocity=0.00

Field roles

Frontier

Rank sensitivity

Stability: volatile; rank range: 54.

Keyword Scores

video world model

world dynamics prediction

world model

generative world model

world simulator

interactive world model

model-based reinforcement learning world model

Resources

Paper