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- license: apache-2.0
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+ ---
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+ license: apache-2.0
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+ ---
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+ ## Interactive Evolution: A Neural-Symbolic Self-Training Framework for Large Language Models
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+ Paper Link: https://arxiv.org/abs/2406.11736
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+ Code Repo: https://github.com/xufangzhi/ENVISIONS
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+ ## 🔥 News
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+ - 🔥🔥🔥 We make public the final checkpoints after self-training ! ! !
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+ ## Note
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+ The self-training process is based on LLaMA2-Chat model serieses and powered by ENVISIONS. The work is still under review.
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+ ## Prompt for Zero-shot Evaluation
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+ ```markdown
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+ You are required to navigate the web. To accomplish the task, use methods in Agent class to generate actions, with the following functions.
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+ type(characters: str): Type a string via the keyboard.
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+ click_xpath(xpath: str): Click an HTML element with a valid XPath.
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+ press(key_type: str): Press a key on the keyboard (enter, space, arrowleft, arrowright, backspace, arrowup, arrowdown, command+a, command+c, command+v).
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+ click_option(xpath: str): Click an option HTML element in a list with a valid XPath.
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+ movemouse(xpath: str): Move the mouse cursor on an HTML element with a valid XPath.
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+ The observation is: <observation>
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+ The action is:
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+ ```
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+ ## Citation
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+ If you find it helpful, please kindly cite the paper.
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+ ```
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+ @misc{xu2024interactive,
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+ title={Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models},
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+ author={Fangzhi Xu and Qiushi Sun and Kanzhi Cheng and Jun Liu and Yu Qiao and Zhiyong Wu},
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+ year={2024},
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+ eprint={2406.11736},
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+ archivePrefix={arXiv},
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+ }
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+ ```
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