embodied ai posts and papers

VABench: Measuring Embodied Spatial Intelligence through Visual Demonstrations, Active Perception, and Metric Control arxiv.org

VA‑Bench is a new benchmark that evaluates general‑purpose multimodal LLMs on the full observe‑reason‑act‑revise loop in embodied robotics, using RGB demonstrations, active camera control, and metric Cartesian commands. The best model reaches 53.9% average task success, showing active perception helps but long‑horizon tasks remain unsolved.

Hugging Face Daily Papersarxiv.orgZhongbo Zhang, Jiayi Jin, Yifan Wang5d1 minpaper

In-Context Robot Learning with VLM Agents arxiv.org

GPT‑Policy is a framework that lets a large vision‑language model (e.g. GPT‑6 Astra) perform in‑context robot learning: a context compiler extracts visual transitions from demos, the VLM proposes tool actions, and a constrained controller verifies and executes them. Real‑robot experiments show that raw video demos improve success rates even without explicit action labels, and that providing align…

Hugging Face Daily Papersarxiv.orgDongzhou Cheng, Taoran Yi, Ye Fang6d1 minpaper

embodied ai

VABench: Measuring Embodied Spatial Intelligence through Visual Demonstrations, Active Perception, and Metric Controlarxiv.org

In-Context Robot Learning with VLM Agentsarxiv.org

VABench: Measuring Embodied Spatial Intelligence through Visual Demonstrations, Active Perception, and Metric Control arxiv.org

In-Context Robot Learning with VLM Agents arxiv.org