Physion-Eval, a new benchmark with nearly 11,000 expert‑annotated video clips, shows that most current AI‑generated videos look realistic but frequently violate basic physics, and that even top multimodal models fail to reliably detect these physical errors.
Speaker Li Yixia from Southern University of Science and Technology presents a talk on using large language models as textual world models, defining a three‑layer evaluation framework and showing through experiments that fine‑tuned models improve next‑state prediction and agent performance, yet face limits tied to behavior coverage and environment complexity.
This article compiles a comprehensive set of embodied AI resources, including large‑scale robot learning datasets such as BC‑Z (32 GB) and DexGraspVLA (7 GB), interactive world‑modeling frameworks like HY‑World 1.5, open‑source LLM deployments, and recent research papers from Nvidia, ByteDance, Xiaomi and leading universities, each with download links and brief summaries.
