arXiv:2606. 15032v2 Announce Type: replace Abstract: World models have become a central abstraction in modern AI.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.
arXiv:2606. 15032v1 Announce Type: new Abstract: World models have rapidly become one of the central abstractions in modern AI.
The paper surveys 160 benchmarks from 2017‑2026 that evaluate predictive embodied intelligence, categorising them into policy suites, embodied agents, world‑model evaluation, and prediction‑to‑action bridges. It finds that most benchmarks are model‑agnostic, rarely compare Vision‑Language‑Action policies to world models, and seldom turn predictions into executed actions. The authors argue that the lack of benchmarks designed to directly test the closed‑loop advantage of world models prevents the field from answering whether such models truly improve robotic performance.
arXiv:2608. 09298v1 Announce Type: cross Abstract: Action-conditioned world models (ACWMs) promise to provide embodied AI with scalable predictive simulators for planning, policy evaluation, and data generation.
arXiv:2607. 00836v1 Announce Type: cross Abstract: World models are increasingly used in embodied intelligence and generative simulation, yet their scope remains ambiguous across communities.
arXiv:2609.16697v1 Announce Type: cross Abstract: World models connect perception and decision-making in embodied intelligence by maintaining hidden state, anticipating consequences, comparing interv...
arXiv:2608.24885v1 Announce Type: cross Abstract: Action-conditioned world models are increasingly used as learned simulators for policy evaluation and improvement, yet their effectiveness rests on a...