3 papers
cs.RO2026
Show-Harness: Just a VLM Agent Can Play Robots
Yanzhe Chen, Zechen Bai, Zhijun Cao +7
Foundation vision-language models (VLMs) exhibit broad intelligence about the world, yet translating this intelligence into robot control remains challenging. We present Show-Harne…
cs.RO2026
Where Success Breaks: Failure-Boundary Learning for Robust Vision-Language-Action Models
Yanzhe Chen, Zhijun Cao, Mike Zheng Shou
Vision-language-action (VLA) models adapted through supervised fine-tuning (SFT) inherit a structural asymmetry: expert demonstrations teach the policy where success behavior lies,…
cs.RO2026
Supervise What Survives: Geometry-Guided VLA Adaptation from Synthetic Robot Videos
Danze Chen, Yanzhe Chen, Qiming Huang +3
Vision-Language-Action (VLA) models require large-scale video-action pairs, yet real teleoperation remains scarce. While generated robot videos offer a scalable alternative, existi…