80 lines
2.7 KiB
Markdown
80 lines
2.7 KiB
Markdown
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---
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license: mit
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language:
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- en
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tags:
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- text-rewriting
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- web
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- generative-engine-optimization
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- geo
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- reinforcement-learning
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- grpo
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- qwen3
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- transformers
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- safetensors
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library_name: transformers
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pipeline_tag: text-generation
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base_model: Qwen/Qwen3-1.7B
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datasets:
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- cx-cmu/E-commerce
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---
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# AutoGEO<sub>Mini</sub> (Qwen1.7B, E-commerce)
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AutoGEO<sub>Mini</sub> (Qwen1.7B, E-commerce) is a GEO model designed to improve how web document is incorporated into answers generated by **LLM-based generative engines**.
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The model rewrites a given document to better match the preferences of generative engines (e.g., GPT, Gemini, Claude), with the goal of increasing the document’s **visibility and coverage** in generated responses, while **preserving the original meaning and factual content**.
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⚠️ This model is trained for the generative engine powered by `gemini-2.5-flash-lite` on dataset `E-commerce`. If you intend to use AutoGEO<sub>Mini</sub> with other types of generative engines or datasets, you must post-train `Qwen/Qwen3-1.7B` using [our code](https://github.com/cxcscmu/AutoGEO).
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This model is part of the **AutoGEO** framework proposed in the paper
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📄 **Paper:** ["What Generative Search Engines Like and How to Optimize Web Content Cooperatively"](https://arxiv.org/abs/2510.11438)
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👥 **Authors:** Yujiang Wu*, Shanshan Zhong*, Yubin Kim, Chenyan Xiong (*Equal contribution)
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🚀 **Code:** [AutoGEO on GitHub](https://github.com/cxcscmu/AutoGEO)
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## Usage
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This model is designed to be used through the [**AutoGEO framework**](https://github.com/cxcscmu/AutoGEO). Try it out in [huggingface Space](https://huggingface.co/spaces/cx-cmu/AutoGEO_Mini) or
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Quick starts:
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```python
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from autogeo.rewriters import rewrite_document
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rewritten_text = rewrite_document(
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document="Input text.",
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dataset="E-commerce",
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engine_llm="gemini",
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model_path="cx-cmu/AutoGEO_mini_Qwen1.7B_ResearchyGEO",
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)
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```
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Evaluation:
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```bash
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python -m autogeo.evaluate \
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--model autogeo_mini \
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--model_path cx-cmu/AutoGEO_mini_Qwen1.7B_ResearchyGEO \
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--dataset E-commerce
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```
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## Related Resources
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* **Paper:** [https://arxiv.org/abs/2510.11438](https://arxiv.org/abs/2510.11438)
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* **Code:** [https://github.com/cxcscmu/AutoGEO](https://github.com/cxcscmu/AutoGEO)
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* **Dataset:** [https://huggingface.co/datasets/cx-cmu/E-commerce](https://huggingface.co/datasets/cx-cmu/E-commerce)
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## Citation
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If you use this model, please cite:
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```bibtex
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@article{wu2025generative,
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title={What Generative Search Engines Like and How to Optimize Web Content Cooperatively},
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author={Wu, Yujiang and Zhong, Shanshan and Kim, Yubin and Xiong, Chenyan},
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journal={arXiv preprint arXiv:2510.11438},
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year={2025}
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}
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```
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