SimpleMemVLA
Collection
A Simple but Effective Native-Video Memory for Vision-Language-Action Models • 11 items • Updated • 1
Datasets:
Search is not available for this dataset
observation.state list | action list | subtask_index int64 0 89 ⌀ | timestamp float32 0 2.95 ⌀ | frame_index int64 0 59 ⌀ | episode_index int64 0 2.5k ⌀ | index int64 0 54.6k ⌀ | task_index int64 0 2 ⌀ |
|---|---|---|---|---|---|---|---|
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End of preview. Expand in Data Studio
SimpleMemVLA Datasets
This repository contains the LeRobot v3 datasets used to train and evaluate SimpleMemVLA, a vision-language-action model with native-video memory for long-horizon robotic manipulation. The datasets cover five benchmarks:
- RMBench (
yinchenghust/rmbench_lerobot) - RoboMME (
yinchenghust/robomme_lerobot) - MIKASA-Robo (
yinchenghust/mikasa_lerobot) - RoboMemArena (
yinchenghust/robomemarena_lerobot) - LIBERO (
yinchenghust/libero_lerobot)
Each dataset includes per-frame subtask supervision and is provided in LeRobot format. For details on the method, see the paper. Code is available at github.com/wadeKeith/SimpleMemVLA. Project page: https://huggingface.co/collections/yinchenghust/simplememvla
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