EasyWAM-MoT-Wan22

EasyWAM-MoT uses separate Video DiT and Action DiT experts whose tokens interact through mixed self-attention. This action-prediction checkpoint was fully fine-tuned on LIBERO with Wan2.2-TI2V-5B as the video backbone.

The corresponding checkpoint was obtained by training with the EasyWAM codebase.

Results

Success rate (%) under the EasyWAM LIBERO evaluation protocol:

Model	Spatial	Object	Goal	Long	Avg.
Full-Parameter
EasyWAM-Unified	99.0	99.4	99.2	98.2	99.0
🔥 EasyWAM-MoT	97.8	98.4	97.6	95.6	97.4
EasyWAM-Hidden	99.4	100.0	97.0	97.8	98.6
LoRA (Rank 128)
EasyWAM-Unified	84.0	97.8	92.0	81.2	88.8
EasyWAM-MoT	96.8	98.8	94.4	90.4	95.1
EasyWAM-Hidden	96.8	99.4	92.6	86.8	93.9

Success rate (%) under the LIBERO-Plus evaluation protocol:

Model	Background	Camera	Language	Layout	Light	Noise	Robot	Avg.
EasyWAM-Unified	55.8	33.7	93.7	80.6	92.2	50.2	71.4	67.5
🔥 EasyWAM-MoT	52.8	20.6	80.4	65.2	85.1	51.5	49.7	56.8
EasyWAM-Hidden	56.8	49.2	95.3	81.0	90.4	58.2	77.4	72.4

Download

hf download OpenMOSS-Team/EasyWAM-MoT-Wan22 \
  easywam_mot_wan22.pt \
  --local-dir ./checkpoints

Evaluation

Prepare Wan2.2, LIBERO, and the matching dataset_stats.json as described in the EasyWAM LIBERO guide, then run:

python experiments/libero/run_libero_manager.py \
  task=libero_easywam_mot_wan22 \
  ckpt=./checkpoints/easywam_mot_wan22.pt \
  EVALUATION.dataset_stats_path=<path-to-matching-dataset_stats.json>

Checkpoint Details

• Architecture: EasyWAM-MoT
• Backbone: Wan2.2-TI2V-5B
• Training: full-parameter fine-tuning
• Dataset: LIBERO, two cameras at 224 px
• Training steps: 20,000
• Action dimension: 7
• State dimension: 8
• Format: EasyWAM PyTorch checkpoint (.pt)

License and Citation

EasyWAM code is released under the MIT License. Use of this checkpoint is also subject to the terms of its base model and training data. If EasyWAM is useful in your research, please cite:

@misc{easywam2026,
  title  = {EasyWAM: A Unified and Efficient Framework for Training and Evaluating World Action Models},
  author = {EasyWAM-Team},
  year   = {2026},
  url    = {https://github.com/OpenMOSS/EasyWAM}
}