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Introducing WM Bench: A Benchmark for Cognitive Intelligence in World Models
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๐ World Model Bench โ does your world model actually think? FID measures realism. FVD measures smoothness. But neither tells you whether the model understood the scene. We just released WM Bench โ the first benchmark for cognitive intelligence in world models. The core question: when a beast charges from 3 meters away, does the model know to sprint โ not walk? Does it respond differently to a human vs an animal? Does it remember the left corridor was blocked two steps ago? Those are cognitive questions. No existing benchmark asks them. So we built one. 3 Pillars ยท 10 Categories ยท 100 Scenarios ยท 1,000-point scale - ๐ P1 Perception (25%) โ Can it read the scene? - ๐ง P2 Cognition (45%) โ Does it predict threats, escalate emotions, utilize memory? - ๐ฅ P3 Embodiment (30%) โ Does the body respond with the right motion? All evaluation is via simple JSON I/O โ no 3D engine, no special hardware. Any model with an API can participate. We also built PROMETHEUS as a live reference implementation โ runs in your browser on a T4, no install needed. Combines FloodDiffusion motion generation with a LLM cognitive brain (Perceive โ Predict โ Decide โ Act). Scored 726/1000 (Grade B) on Track C โ the only directly verified model so far. Submissions from other teams very welcome. --- ๐ Dataset โ https://huggingface.co/datasets/FINAL-Bench/World-Model ๐ Demo โ https://huggingface.co/spaces/FINAL-Bench/World-Model ๐ Leaderboard โ https://huggingface.co/spaces/FINAL-Bench/worldmodel-bench ๐ Article โ https://huggingface.co/blog/FINAL-Bench/world-model Part of the FINAL Bench Family โ alongside FINAL Bench (Feb 2026). Feedback on rubrics and missing models always welcome!
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