SimpleMemVLA
Collection
A Simple but Effective Native-Video Memory for Vision-Language-Action Models • 11 items • Updated • 1
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SimpleMemVLA Dataset
This repository contains the datasets used in the paper SimpleMemVLA: A Simple but Effective Native-Video Memory for Vision-Language-Action Models. The datasets are provided in LeRobot v3 format and include per-frame sub-task annotations, camera observations, actions, and proprioceptive state for long-horizon robotic manipulation benchmarks.
- Paper: Hugging Face paper page (arXiv)
- Project page: https://huggingface.co/collections/yinchenghust/simplememvla
- Code: https://github.com/wadeKeith/SimpleMemVLA
The datasets cover the following benchmarks: RMBench, RoboMME, MIKASA-Robo, RoboMemArena, and LIBERO. For download instructions, training, and evaluation details, see the GitHub repository.
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