MolmoAct: Action Reasoning for Robots
Автор: AI Research Roundup
Загружено: 2025-08-15
Просмотров: 39
Описание:
In this AI Research Roundup episode, Alex discusses the paper:
'MolmoAct: Action Reasoning Models that can Reason in Space(2508.07917v2)'
MolmoAct introduces Action Reasoning Models (ARMs) that unify perception, planning, and control in a three-stage pipeline. The model encodes depth-aware perception tokens, produces editable spatial trajectory plans, and executes precise low-level actions—making behavior explainable and steerable. It achieves state-of-the-art results across simulation and real-world tasks, with strong zero-shot performance, long-horizon gains, and superior OOD generalization and human preference scores. The authors also release the MolmoAct Dataset with 10,000+ robot trajectories, boosting general performance by 5.5%.
Paper URL: https://arxiv.org/pdf/2508.07917
#AI #MachineLearning #DeepLearning #Robotics #RobotPlanning #EmbodiedAI
Повторяем попытку...
Доступные форматы для скачивания:
Скачать видео
-
Информация по загрузке:
![Как внимание стало настолько эффективным [GQA/MLA/DSA]](https://image.4k-video.ru/id-video/Y-o545eYjXM)
