World models don't learn object permanence from scale: it has to be taught

A research paper treats object permanence, knowing that something still exists when it's hidden, as a training problem for video world models. The authors built 150 cognitive tasks and about 1.5 million generated clips of objects being hidden and interacting physically.

Fine-tuning a 16-billion-parameter model, PWM-WROP, on this synthetic data produced the top-ranked model for continuing a video in a human evaluation.

The finding

• object permanence did not emerge from scale; it had to be trained in explicitly
• understanding of collisions and physics still lags

The paper was listed on Hugging Face Daily Papers, with affiliations including CMU.

Why it matters

There is a running argument over whether world models actually understand physics. This is a concrete negative result for "just make it bigger", rather than a marketing claim.