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NeurIPS 2026Ai2 Purdue U Wisconsin - Madison Department of Computer Science, Rutgers Flow matching

Learning Visual Feature-Based World Models via Residual Latent Action

Residual Latent Action predicts visual feature dynamics via flow matching, outperforming diffusion world models with orders-of-magnitude faster inference and enabling offline robot learning from videos.

Xinyu Zhang, Zhengtong Xu, Yutian Tao, Yeping Wang and 2 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 3 on Hugging Face · Code ★ 47

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lenient 5/5

medium 9/10

strict 1/5

Neural Bayesian Filtering

Neural Bayesian Filtering maintains hidden-state beliefs via learned embeddings and particle-style updates, tracking multimodal distributions efficiently in partially observable environments.

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AI panel: 5 of 20 reviewers recommend it

lenient 4/5

medium 1/10

strict 0/5