Baoyu Li ✈️ CoRL 2026(@BaoyuLi6):Egocentric human data is abundant, but human motion is not always positive supervision for robot policy due to embodiment gaps. Naive BC co-training can HURT performance ☹️. 🌟Our key finding in **EgoWAM**: the state-prediction branch of a World Action Model effectively bridges this embodiment gap, enabling robot performance to scale with diverse **in-the-wild** human data. 💡The key question then becomes: what world representation transfers best across embodiments? 👇🏻Let’s take a deep dive into it: 🌐 https://t.co/VnhUs8CFKf 🧵[1/]

Baoyu Li ✈️ CoRL 2026@BaoyuLi6

2026.07.08 15:35

Egocentric human data is abundant, but human motion is not always positive supervision for robot policy due to embodiment gaps. Naive BC co-training can HURT performance ☹️. 🌟Our key finding in **EgoWAM**: the state-prediction branch of a World Action Model effectively bridges this embodiment gap, enabling robot performance to scale with diverse **in-the-wild** human data. 💡The key question then becomes: what world representation transfers best across embodiments? 👇🏻Let’s take a deep dive into it: 🌐 🧵[1/]