| # In-Context Imitation Learning via Next-Token Prediction |
| by <a href="https://max-fu.github.io">Max (Letian) Fu*</a>, <a href="https://qingh097.github.io/">Huang Huang*</a>, <a href="https://www.linkedin.com/in/gaurav-datta/">Gaurav Datta*</a>, <a href="https://yunliangchen.github.io/">Lawrence Yunliang Chen</a>, <a href="https://autolab.berkeley.edu/people">William Chung-Ho Panitch</a>, <a href="https://fangchenliu.github.io/">Fangchen Liu</a>, <a href="https://www.research.autodesk.com/people/hui-li/">Hui Li</a>, and <a href="https://goldberg.berkeley.edu">Ken Goldberg</a> at UC Berkeley and Autodesk (*equal contribution). |
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| [[Paper](https://icrt.dev/files/icrt.pdf)] | [[Project Page](https://icrt.dev/)] | [[Checkpoints](https://huggingface.co/mlfu7/ICRT)] | [[Dataset](https://huggingface.co/datasets/Ravenh97/ICRT-MT)] | [[Citation](#citation)] |
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| This repo contains the checkpoints for *In-Context Imitation Learning via Next-Token Prediction*. We investigate how to bring few-shot, in-context learning capability that exists in next-token prediction models (i.e. GPT) into real-robot imitation learning policies. |
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| In particular, we store the pre-trained vision encoder and ICRT model separately. Please find them in [encoder](crossmae_rtx/cross-mae-rtx-vitb.pth), [ICRT](icrt_vitb_droid_pretrained/icrt_vitb_droid_pretrained.pth), and [ICRT-Llama7B](icrt_llama7b_lora/icrt_llama7b_lora.pth). |
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| Please refer to the [code](https://github.com/Max-Fu/icrt) on installing the repo, training and inferencing the model. |
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| ## Dataset Structure |
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| ``` |
| ICRT-MT |
| ├── merged_data_part1.hdf5 |
| │ ├── episode_1 |
| │ │ ├── observation |
| │ │ ├── exterior_image_1_left |
| │ │ └── exterior_image_2_left |
| │ │ └── wrist_image_left |
| │ │ └── cartesian_position |
| │ │ └── gripper_position |
| │ │ └── joint_position |
| │ │ ├── action |
| │ │ ├── cartesian_velocity |
| │ │ └── gripper_velocity |
| │ │ └── joint_velocity |
| │ │ └── cartesian_position |
| │ │ └── gripper_position |
| │ │ └── joint_position |
| │ │ ├── language_instruction |
| │ │ ├── language_instruction_2 |
| │ │ ├── language_instruction_3 |
| │ │ ├── language_embedding |
| │ │ ├── language_embedding_2 |
| │ │ ├── language_embedding_3 |
| │ │ ... |
| │ ├── episode_2 |
| │ │ ... |
| │ └── episode_3 |
| │ ... |
| └── merged_data_part1_keys.json |
| ... |
| ``` |
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| ## Citation |
| Please give us a star 🌟 on Github to support us! |
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| Please cite our work if you find our work inspiring or use our code in your work: |
| ``` |
| @article{fu2024icrt, |
| title={In-Context Imitation Learning via Next-Token Prediction}, |
| author={Letian Fu and Huang Huang and Gaurav Datta and Lawrence Yunliang Chen and William Chung-Ho Panitch and Fangchen Liu and Hui Li and Ken Goldberg}, |
| journal={arXiv preprint arXiv:2408.15980}, |
| year={2024} |
| } |
| ``` |
