English

Static and Plugged: Make Embodied Evaluation Simple

Computer Vision and Pattern Recognition 2025-08-12 v1

Abstract

Embodied intelligence is advancing rapidly, driving the need for efficient evaluation. Current benchmarks typically rely on interactive simulated environments or real-world setups, which are costly, fragmented, and hard to scale. To address this, we introduce StaticEmbodiedBench, a plug-and-play benchmark that enables unified evaluation using static scene representations. Covering 42 diverse scenarios and 8 core dimensions, it supports scalable and comprehensive assessment through a simple interface. Furthermore, we evaluate 19 Vision-Language Models (VLMs) and 11 Vision-Language-Action models (VLAs), establishing the first unified static leaderboard for Embodied intelligence. Moreover, we release a subset of 200 samples from our benchmark to accelerate the development of embodied intelligence.

Keywords

Cite

@article{arxiv.2508.06553,
  title  = {Static and Plugged: Make Embodied Evaluation Simple},
  author = {Jiahao Xiao and Jianbo Zhang and BoWen Yan and Shengyu Guo and Tongrui Ye and Kaiwei Zhang and Zicheng Zhang and Xiaohong Liu and Zhengxue Cheng and Lei Fan and Chuyi Li and Guangtao Zhai},
  journal= {arXiv preprint arXiv:2508.06553},
  year   = {2025}
}
R2 v1 2026-07-01T04:41:36.361Z