next-forcing-posttrain-robotwin

Next Forcing — RoboTwin Post-trained Checkpoint

Post-trained checkpoint for Next Forcing: Causal World Modeling with Multi-Chunk Prediction, evaluated on the RoboTwin 2.0 benchmark.

• 📄 Paper: https://arxiv.org/pdf/2606.11187
• 🌐 Project page: https://gangweix.github.io/next-forcing/
• 💻 Code: https://github.com/gangweix/next-forcing

Model Description

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.

Results

Average success rate on RoboTwin 2.0:

Repository Layout

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.

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:

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

@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}
}