LingBot-Video Training: 6D Physical Rewards and Real Robot Data
thetripathi58 · x · 2026-07-09
LingBot-Video changes the traditional scoring mechanism of video models that only pursue visual aesthetics. It adopts a single-step GRPO algorithm and introduces 6 precise reward signals: visual quality, image-text alignment, dynamics, motion coherence, human action consistency, and physical plausibility, ensuring the model understands real physical laws.
To prevent the model from "faking" physics, the team trained it using over 70,000 hours of real robot data, including real-hand operations, walking trajectories, and first-person perspectives from humanoid and quadruped robots.
Related event: Ant Group Open-Sources LingBot-Video for Embodied AI(26 posts)→
More from Embodied
- Amazon and Google sold 600M+ smart speakers, so why no AGI-era successor? — julianlehr · 2026-09-11
- ECCV26 Oral: Flow Matching Enables Single-Stage Multi-View Point Cloud Registration — ducha_aiki · 2026-09-11
- Polish developers build iPhone app that detects nearby Meta smart glasses — Low-Honeydew6483 · 2026-09-11
- Ant's Afu health AI hits 150M users, unveils AI+hardware health alliance at Bund Summit — APPSO · 2026-09-11
- Johns Hopkins Launches Full-Stack Hands-on Robot Learning Class with SO-101 Arm Kits — _krishna_murthy · 2026-09-11
- SyncWorld: In-Context Robot World Model Simulates Unseen Views and Embodiments Zero-Shot — ChongZzZhang · 2026-09-11