MIND: Benchmarking Memory Consistency and Action Control in World Models
World models aim to understand, remember, and predict dynamic visual environments, yet a unified benchmark for evaluating their fundamental abilities remains lacking. To address this gap, we introduce MIND, the first open-domain closed-loop revisited benchmark for evaluating Memory consIstency and action coNtrol in worlD models. MIND contains 250 high-quality videos at 1080p and 24 FPS, including 100 (first-person) + 100 (third-person) video clips under a shared action space and 25 + 25 clips across varied action spaces covering eight diverse scenes. We design an efficient evaluation framework to measure two core abilities: memory consistency and action control, capturing temporal stabili...
| Authors | Yixuan Ye, Xuanyu Lu, Yuxin Jiang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 February 2026 |
| Last updated at source | 11 February 2026 |
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