README.md

metadata

pretty_name: GlanceWAM reproduction bundle
license: other
task_categories:
  - robotics
tags:
  - robotics
  - vision-language-action
  - world-model
  - libero
  - robocasa
  - arxiv:2608.23927

GlanceWAM reproduction bundle

Paper: GlanceWAM: Sparse Test-Time Imagination for World-Action Models

Everything needed to reproduce the GlanceWAM results on LIBERO and RoboCasa kitchen.

datasets/     LeRobot v3 datasets, UMT5 text caches included (glancewam_cache/)
checkpoints/  released checkpoints, one directory per run

Point the code at this directory:

export DATA_ROOT=/data/glancewam_release/datasets           # training + precompute
ln -s /data/glancewam_release/checkpoints  <repo>/results/Checkpoints

Checkpoints

Directory	Benchmark	Reported
glancewam_robocasa_kitchen	RoboCasa kitchen, 24 tasks x 50 episodes	0.721
glancewam_libero	LIBERO 4-in-1, 4 suites x 500 episodes	0.989

Kitchen run-to-run noise is ~0.02 (the environment is paired but the policy is unseeded), so treat anything within ~+/-0.02 as a match. LIBERO is saturated; differences under ~0.005 are noise.

Datasets

Directory	Used by
libero_{spatial,object,goal,10}_no_noops_1.0.0_lerobot	LIBERO (mixture libero_all)
robocasa_cosmos_kitchen/	RoboCasa kitchen, 24 per-task datasets (mixture robocasa_kitchen_all)

Each dataset already carries its precomputed UMT5 text cache under <dataset>/glancewam_cache/t5/Skywork_SkyReels-V2-DF-1.3B-540P-Diffusers_L512, so training can run with RESIDENT_TEXT_TABLE=True (the default) without running the precompute step first.

The dataset trees are hard-linked from /data/lerobot_v3, so they cost no extra disk on this machine; copying the directory elsewhere produces independent full copies.

Code

https://github.com/linhanwang/GlanceWAM

# everything (21 GB)
hf download LinhanWang/GlanceWAM --repo-type dataset --local-dir ./glancewam_bundle

# or just one benchmark
hf download LinhanWang/GlanceWAM --repo-type dataset --local-dir ./glancewam_bundle \
    --include "checkpoints/glancewam_libero/*" "datasets/libero_*"                    # 5.0 GB
hf download LinhanWang/GlanceWAM --repo-type dataset --local-dir ./glancewam_bundle \
    --include "checkpoints/glancewam_robocasa_kitchen/*" \
              "datasets/robocasa_cosmos_kitchen/*"                                     # 16.2 GB

# then, from the code checkout
mkdir -p results
ln -s /abs/path/to/glancewam_bundle/datasets     results/Datasets
ln -s /abs/path/to/glancewam_bundle/checkpoints  results/Checkpoints

Attribution

The datasets here are derived from third-party releases and remain subject to their original terms: LIBERO (Lifelong Robot Learning, MIT) and the RoboCasa kitchen task suite as distributed by NVIDIA's cosmos-policy release (RoboCasa Team, MIT). The checkpoints are fine-tuned from SkyReels-V2-DF-1.3B-540P (Skywork) and inherit that model's terms. The GlanceWAM code itself is MIT-licensed; see the code repository.