You can deploy this model and start earning money today!

SemyonXu616/
VGAS-5-shot

Name: VGAS-5-shot
Availability: InStock

lerobot

safetensors

robotics

vision-language-action

Views

No views yet

VGAS and VGAS+ — 5-Shot LIBERO Checkpoints

This repository contains the checkpoints used to evaluate VGAS and VGAS+ on the 5-shot LIBERO benchmark. The implementation is available in the VGAS code repository.

Repository layout

text

smolvla/5_SHOT/pretrained_model/       # Shared 5-shot SmolVLA policy
{suite}/vgas_critic/last.ckpt          # VGAS inference-time critic
{suite}/vgas_plus/pretrained_model/    # Distilled VGAS+ policy

Here, {suite} is one of goal, object, spatial, or long (long corresponds to libero_10). VGAS uses the shared SmolVLA policy together with the suite-specific critic for Best-of-N selection. The SFT policy is frozen while training the VGAS critic. VGAS+ directly executes the distilled policy and does not require a critic or inference-time reranking.

VGAS+ checkpoints

Directory	LIBERO suite
`goal/vgas_plus/pretrained_model`	`libero_goal`
`object/vgas_plus/pretrained_model`	`libero_object`
`spatial/vgas_plus/pretrained_model`	`libero_spatial`
`long/vgas_plus/pretrained_model`	`libero_10`

Download one policy with huggingface_hub:

python

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="SemyonXu616/VGAS-5-shot",
    allow_patterns=["goal/vgas_plus/pretrained_model/*"],
    local_dir="checkpoints/VGAS-5-shot",
)

The downloaded policy directory can be passed directly as POLICY_PATH to the VGAS+ evaluation scripts in the code repository.

Citation

bibtex

@article{xu2026vgas,
  title   = {VGAS: Value-Guided Action-Chunk Selection for Few-Shot Vision-Language-Action Adaptation},
  author  = {Xu, Changhua and Yu, En and Xuan, Junyu and Lu, Jie},
  journal = {arXiv preprint arXiv:2602.07399},
  year    = {2026}
}

The VGAS+ citation will be added when its preprint is available.