Instructions to use LiAuto-DSR/avavla-calvin-abc2d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiAuto-DSR/avavla-calvin-abc2d with Transformers:
# Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("LiAuto-DSR/avavla-calvin-abc2d", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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pipeline_tag: robotics
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library_name: transformers
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---
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# AVA-VLA: Improving Vision-Language-Action models with Active Visual Attention
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This repository contains the AVA-VLA checkpoint trained on CALVIN ABC→D setting, as described in [AVA-VLA: Improving Vision-Language-Action models with Active Visual Attention](https://arxiv.org/abs/2511.18960). AVA-VLA reformulates vision-language-action policy learning from a partially observable perspective and uses a recurrent state to summarize task history for action generation.
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Project Page: https://liauto-dsr.github.io/AVA-VLA-Page/
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Code: https://github.com/LiAuto-DSR/AVA-VLA
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## Citation
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```bibtex
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@article{xiao2025ava,
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title={AVA-VLA: Improving Vision-Language-Action models with Active Visual Attention},
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author={Xiao, Lei and Li, Jifeng and Gao, Juntao and Ye, Feiyang and Jin, Yan and Qian, Jingjing and Zhang, Jing and Wu, Yong and Yu, Xiaoyuan},
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journal={arXiv preprint arXiv:2511.18960},
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year={2025}
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}
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```
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