html,body{height:auto!important;overflow:auto!important} [data-requires-script]{display:none!important} .reader{position:relative!important;overflow:visible!important;min-height:100vh} .reader-frame{height:auto!important;max-height:none!important;margin:auto} .reader-stage,.lesson-reader-stage{position:relative!important;inset:auto!important;overflow:visible!important} .reader-track,.lesson-track{position:relative!important;inset:auto!important;display:block!important;height:auto!important;transform:none!important} .reader-slide,.reader-panel,.lesson-panel{width:100%!important;height:auto!important;min-height:0!important;overflow:visible!important;content-visibility:visible!important} .reader-scroll,.lesson-panel-scroll{position:relative!important;inset:auto!important;height:auto!important;overflow:visible!important;padding-bottom:32px!important} .reader-tabs,.reader-tap,.reader-detail-dock,.card-dock{display:none!important} .lg-screen,.lg-feed,.lg-page,.dr-screen .lg-page{height:auto!important;overflow:visible!important} .lg-page{min-height:100vh} @media(min-width:1000px){.lg-page{min-height:0!important}}

Author

Peng Gao

Papers that credit Peng Gao in their source bylines. Matching names may refer to different researchers.

1 results

PaperRobotics
Robot models learn from executed action alternatives to predict failures
CureWM repairs released robot world models with executed action alternatives, improving success–failure prediction in several tested settings.
Added to Chiosa Oct 08, 2026
#robot-learning #real-world-deployment #future-prediction

Peng Gao

Robot models learn from executed action alternatives to predict failures