LDR Video World Model Extrapolates Dynamics Beyond Training Distribution
Scobleizer · x · 2026-08-25
Latent Dynamics Reasoning (LDR) is a new video world model designed to understand "how the world evolves." Instead of predicting future frames directly, it maps past frames to structured latent states and rolls them forward via kinematic integration, learning only the high-order motion residuals. The authors claim LDR is the first video world model to extrapolate learned dynamics beyond its training distribution. Paper, code, models, and datasets are now publicly available.
Related event: Adobe's LDR World Model Extrapolates Beyond Training Distribution(3 posts)→
More from Research
- Cohere Labs world model course session 4: DreamerV1-V4 architectures in one go — Cohere_Labs · 2026-10-16
- Reasonable post-trains Nemotron 3.5 on 3,000 Verus proofs, lifting pass@1 ~30 points to 73.3% — fhuszar · 2026-10-16
- GPT-6.1 Sol audit finds 6% of arXiv papers had false main theorems, down to 1.5% recently — nitarshan · 2026-10-16
- One tiny word changes the conversation: how LLMs pick up on 'just' — StellaLisy · 2026-10-16
- SEAR: first large-scale controlled study of self-evolving robot agents, 7 LLMs, 330 tasks — xiye_nlp · 2026-10-16
- After Claude-assisted elliptic curve records fell, EC Rank challenge opens 156 record slots — Jsevillamol · 2026-10-16