research
The Game Engine Became the Spatial Reward Source
RLHEV proposes combining deterministic engine checks with developer acceptance feedback for world-model post-training.
Summary
RLHEV proposes combining deterministic engine checks with developer acceptance feedback for world-model post-training.
The position paper argues that collision, physics, navigation and bounded playability provide denser verification than fuzzy visual similarity scores. It proposes a data engine rather than reporting a completed benchmark or deployed model.
Why it matters
RLHEV proposes combining deterministic engine checks with developer acceptance feedback for world-model post-training.
Limits and context
No additional limitation was separately recorded.
Key claims
RLHEV proposes combining deterministic engine checks with developer acceptance feedback for world-model post-training.
Evidence: source-2026-08-27-021
Sources
- arXiv preprint 2608.25518arXiv · primary research
Corrections
No corrections have been recorded for this story.