Next Forcing addresses the myopic supervision problem in autoregressive video world models: next-chunk denoising tends to learn local appearance shortcuts instead of long-range dynamics, especially at high frame rates. Lightweight Multi-Chunk Prediction (MCP) modules predict multiple future chunks through a causal chain during training, providing dense temporal supervision to the backbone.

This checkpoint is the RoboTwin post-trained model, built on top of the LingBot-VA codebase. It was post-trained from gangweix/next-forcing-base.


Parameters	6.7B (BF16)
Backbone layers	30
MCP depths	3 (`mcp_blocks_per_depth=3`, collect layers `[3, 11, 19, 29]`)
Benchmark	RoboTwin 2.0, 50 bimanual manipulation tasks
Initialized from	`next-forcing-base` (5.1B)

Results

Average success rate on RoboTwin 2.0:

Setting	LingBot-VA	Next Forcing
Clean	92.9	94.1
Random	91.5	93.5

Repository Layout

text

transformer/     Next Forcing backbone with MCP modules (enable_mcp=true)
vae/
text_encoder/
tokenizer/

Usage

Clone the code and install the dependencies as described in the repository README.

bash

python -m pip install "huggingface_hub[cli]"
hf download gangweix/next-forcing-posttrain-robotwin \
  --local-dir ./checkpoints/next-forcing-posttrain-robotwin

The evaluation code resolves model subfolders by path, so point NEXT_FORCING_MODEL_PATH at the local directory, not at the Hub repository id:

bash

export NEXT_FORCING_MODEL_PATH=$PWD/checkpoints/next-forcing-posttrain-robotwin
export ROBOTWIN_ROOT=/path/to/your/RoboTwin

# Start the inference server on one GPU
CUDA_VISIBLE_DEVICES=0 bash evaluation/robotwin/launch_server.sh

# In another terminal, evaluate one task for 100 trials
bash evaluation/robotwin/launch_client.sh /path/to/eval_results adjust_bottle

RoboTwin evaluation requires a working RoboTwin 2.0 installation; see the official guide.

License

Released under the Apache License 2.0. Next Forcing is developed on top of the LingBot-VA codebase; please retain the upstream attribution and license when redistributing.

Citation

bibtex

@article{xu2026next,
  title={Next Forcing: Causal World Modeling with Multi-Chunk Prediction},
  author={Xu, Gangwei and Zhang, Qihang and Zhou, Jiaming and Zhu, Xing and Shen, Yujun and Yang, Xin and Xu, Yinghao},
  journal={arXiv preprint arXiv:2606.11187},
  year={2026}
}