BAAI-Humanoid/DECO_sim

DECO: Decoupled Multimodal Diffusion Transformer for Bimanual Dexterous Manipulation with a Plugin Tactile Adapter

All checkpoints use a compact model of about 80M parameters and achieve near-SOTA success rates on their respective benchmarks.

Checkpoints

File	Benchmark	Description
libero.pth	LIBERO	Vision-only policy
dexjoco.pth	DexJoCo	Vision-only policy
univtac.pth	UniVTAC	Vision-only policy
univtac-p.pth	UniVTAC	Vision policy + plugin tactile adapter
robotwin.pth	RoboTwin	Vision policy with a T5 text encoder

Results

LIBERO

Success rates (50 trials per task):

Model	Spatial	Object	Goal	Long	Average
DECO	94.2%	99.4%	96.8%	86.4%	94.2%

DexJoCo

Success rates (50 trials per task); /B denotes a bimanual task:

Model	Hammer Nail	Click Mouse	Pick Bucket	Pinch Tongs	Fold Glasses	Water Plant	Unlock iPad /B	Hanoi /B	Assembly /B	Microwave /B	Photograph /B	Average
DECO (rand-obj)	68%	90%	80%	46%	50%	88%	40%	18%	0%	64%	76%	56.4%
DECO (rand-full)	66%	82%	88%	52%	52%	80%	40%	24%	16%	72%	66%	58%

UniVTAC

Success rates (100 trials per task):

Model	grasp_classify	lift_can	lift_bottle	pull_out_key	put_bottle_in_shelf	insert_hole	insert_tube	insert_HDMI	Average
DECO (vision)	96.0%	99.0%	100.0%	96.0%	90.0%	63.0%	88.0%	25.0%	82.1%
DECO.p (+tactile)	99.0%	99.0%	100.0%	96.0%	93.0%	59.0%	88.0%	23.0%	82.1%

RoboTwin

Success rates (%) on the 50 RoboTwin dual-arm tasks under the Seen and Unseen settings (100 trials per task):

Task	Seen Clean	Seen Randomized	Seen Avg.	Unseen Clean	Unseen Randomized	Unseen Avg.
adjust_bottle	100.00%	100.00%	100.00%	99.00%	99.00%	99.00%
beat_block_hammer	96.00%	86.00%	91.00%	98.00%	90.00%	94.00%
blocks_ranking_rgb	72.00%	65.00%	68.50%	75.00%	65.00%	70.00%
blocks_ranking_size	44.00%	38.00%	41.00%	42.00%	40.00%	41.00%
click_alarmclock	95.00%	88.00%	91.50%	93.00%	92.00%	92.50%
click_bell	95.00%	95.00%	95.00%	94.00%	90.00%	92.00%
dump_bin_bigbin	96.00%	95.00%	95.50%	98.00%	97.00%	97.50%
grab_roller	98.00%	99.00%	98.50%	100.00%	99.00%	99.50%
handover_block	97.00%	86.00%	91.50%	97.00%	87.00%	92.00%
handover_mic	100.00%	96.00%	98.00%	99.00%	97.00%	98.00%
hanging_mug	43.00%	26.00%	34.50%	30.00%	33.00%	31.50%
lift_pot	100.00%	100.00%	100.00%	100.00%	99.00%	99.50%
move_can_pot	85.00%	83.00%	84.00%	77.00%	79.00%	78.00%
move_pillbottle_pad	93.00%	92.00%	92.50%	91.00%	88.00%	89.50%
move_playingcard_away	100.00%	96.00%	98.00%	98.00%	99.00%	98.50%
move_stapler_pad	85.00%	87.00%	86.00%	87.00%	85.00%	86.00%
open_laptop	96.00%	100.00%	98.00%	96.00%	100.00%	98.00%
open_microwave	88.00%	84.00%	86.00%	85.00%	86.00%	85.50%
pick_diverse_bottles	84.00%	77.00%	80.50%	85.00%	74.00%	79.50%
pick_dual_bottles	90.00%	92.00%	91.00%	93.00%	93.00%	93.00%
place_a2b_left	63.00%	59.00%	61.00%	62.00%	58.00%	60.00%
place_a2b_right	53.00%	47.00%	50.00%	49.00%	50.00%	49.50%
place_bread_basket	92.00%	81.00%	86.50%	92.00%	86.00%	89.00%
place_bread_skillet	91.00%	81.00%	86.00%	91.00%	83.00%	87.00%
place_burger_fries	97.00%	100.00%	98.50%	99.00%	98.00%	98.50%
place_can_basket	79.00%	71.00%	75.00%	78.00%	74.00%	76.00%
place_cans_plasticbox	100.00%	99.00%	99.50%	100.00%	99.00%	99.50%
place_container_plate	99.00%	97.00%	98.00%	95.00%	97.00%	96.00%
place_dual_shoes	85.00%	81.00%	83.00%	79.00%	76.00%	77.50%
place_empty_cup	99.00%	100.00%	99.50%	97.00%	98.00%	97.50%
place_fan	92.00%	93.00%	92.50%	93.00%	99.00%	96.00%
place_mouse_pad	83.00%	75.00%	79.00%	85.00%	74.00%	79.50%
place_object_basket	89.00%	89.00%	89.00%	86.00%	83.00%	84.50%
place_object_scale	77.00%	68.00%	72.50%	77.00%	67.00%	72.00%
place_object_stand	90.00%	87.00%	88.50%	96.00%	85.00%	90.50%
place_phone_stand	83.00%	85.00%	84.00%	77.00%	83.00%	80.00%
place_shoe	98.00%	98.00%	98.00%	98.00%	100.00%	99.00%
press_stapler	82.00%	84.00%	83.00%	81.00%	87.00%	84.00%
put_bottles_dustbin	87.00%	88.00%	87.50%	83.00%	86.00%	84.50%
put_object_cabinet	75.00%	84.00%	79.50%	84.00%	79.00%	81.50%
rotate_qrcode	85.00%	93.00%	89.00%	85.00%	87.00%	86.00%
scan_object	88.00%	89.00%	88.50%	92.00%	90.00%	91.00%
shake_bottle	100.00%	98.00%	99.00%	100.00%	98.00%	99.00%
shake_bottle_horizontally	100.00%	99.00%	99.50%	100.00%	99.00%	99.50%
stack_blocks_three	85.00%	83.00%	84.00%	85.00%	81.00%	83.00%
stack_blocks_two	96.00%	99.00%	97.50%	97.00%	98.00%	97.50%
stack_bowls_three	83.00%	83.00%	83.00%	81.00%	78.00%	79.50%
stack_bowls_two	96.00%	95.00%	95.50%	99.00%	98.00%	98.50%
stamp_seal	61.00%	75.00%	68.00%	69.00%	71.00%	70.00%
turn_switch	63.00%	72.00%	67.50%	69.00%	64.00%	66.50%
Overall	86.56%	84.76%	85.66%	86.32%	84.36%	85.34%

Usage

Download all checkpoints:

hf download BAAI-Humanoid/DECO_sim --repo-type model --local-dir ./sim_ckpt/

Load a checkpoint into the DECO policy and evaluate it with the corresponding benchmark configuration. The training and evaluation code lives in the DECO repository:

• LIBERO, DexJoCo, and UniVTAC are on the sim branch.
• RoboTwin is on the robotwin branch.

Citation

@article{li2026deco,
  title={DECO: Decoupled Multimodal Diffusion Transformer for Bimanual Dexterous Manipulation with a Plugin Tactile Adapter},
  author={Xukun Li and Yu Sun and Lei Zhang and Bosheng Huang and Yibo Peng and Yuan Meng and Haojun Jiang and Shaoxuan Xie and Guacai Yao and Alois Knoll and Zhenshan Bing and Xinlong Wang and Zhenguo Sun},
  journal={arXiv preprint arXiv:2602.05513},
  year={2026}
}

License

Apache 2.0