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This research introduces Physis-Lang, a framework that embeds explicit physical reasoning directly into video generation captions to correct common simulation errors like objects passing through walls or fluids behaving incorrectly. By treating physics as an optimizable language representation rather than relying solely on visual signals, the system successfully pushes Cosmos 3 past Veo 3.1 on public physics benchmarks. The approach demonstrates a significant step forward in aligning generative video models with real-world physical laws through linguistic conditioning.

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NVIDIA Researchers Introduce Physis-Lang: Self-Evolving Physical Language That Lifts Cosmos 3 Past Veo 3.1 on Physics Benchmarks

MarkTechPostSeptember 30, 20265 min read

Video world models can render convincing clips that still break physics. Butter spreads like paint. Balls pass through walls. A team from NVIDIA, MIT and the University of Oxford argues the fix can come from language itself, not from extra visual, latent or numerical signals. Their framework, Physis-Lang, treats physical language as a shared, optimizable […] The post NVIDIA Researchers Introduce Physis-Lang: Self-Evolving Physical Language That Lifts Cosmos 3 Past Veo 3.1 on Physics Benchmarks appeared first on MarkTechPost.

Video world models can render convincing clips that still break physics. Butter spreads like paint. Balls pass through walls. A team from NVIDIA, MIT and the University of Oxford argues the fix can come from language itself, not from extra visual, latent or numerical signals. Their framework, Physis-Lang, treats physical language as a shared, optimizable representation. The same text drives data curation, model training and inference. On the public Physics-IQ Verified leaderboard snapshot dated September 29, 2026, Physis-Lang on Cosmos3-Super ranks first at 48.2 ±…

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