GPT-6 Astra 登顶 EgoHome 手部动作理解基准
Perceptron AI 发布开源基准 EgoHome，专门评测模型对家务视频中手部动作的细粒度理解，包含 750 余个时长不足 500 毫秒的片段，并标注手部框、子任务、手部动作与手部描述四类信息。GPT-6 Astra 在该基准上排名第一。该基准直接服务于机器人从人类视频中学习操作技能的数据标注环节，标注质量决定机器人训练的正确性。
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Rohan Paul (@rohanpaul_ai) · 2026-11-10 21
GPT-6 Astra came out on top in EgoHome, a new benchmark from Perceptron AI, that tests whether AI can follow what human hands do in chore videos, the skill robots need to learn from people.
AI can tell you someone is washing dishes, but not what their hands are doing, and robots need the second part.
This kind of benchmarks are so important because Robotics training now happen on large amounts of human video, and AI is used to label those videos automatically (“left hand picks up sponge, right hand turns tap”). If those labels are wrong, the robots learn wrong.
↳ 引用 @perceptroninc (Perceptron AI): Introducing EgoHome: a new open benchmark for dense, sub-second egocentric understanding.
Human-annotated household-chore video with 4 annotation types on every clip: hand boxes, subtasks, hand actions, hand captions.
It features over 750 segments under 500ms.
Data, metrics, and judge prompts are all open. 🧵
