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README.md
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@@ -25,7 +25,7 @@ IntentNet is trained through Supervised Fine-Tuning (SFT) to improve upon the ba
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- Label the AI intention with binary labels, which indicates whether the AI thought decevptive or not (0: non-deceptive, 1:deceptive).
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## Links
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- [Paper](https://arxiv.org/abs/2504.
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- [GitHub Repository](https://github.com/Simoniracle/OpenDeception-Framework) - Source code and framework
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## Usage
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author={Wu, Yichen and Gao, Qianqian and Pan, Xudong and Hong, Geng and Yang, Min},
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journal={arXiv preprint arXiv:},
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year={2026},
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url={https://arxiv.org/abs/2504.
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}
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```
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## Details
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For more information, visit the [GitHub repository](https://github.com/Simoniracle/OpenDeception-Framework) or read the [paper](https://arxiv.org/abs/2504.
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### Framework versions
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- Label the AI intention with binary labels, which indicates whether the AI thought decevptive or not (0: non-deceptive, 1:deceptive).
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## Links
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- [Paper](https://arxiv.org/abs/2504.13707v3) - arXiv: 2504.13707v3
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- [GitHub Repository](https://github.com/Simoniracle/OpenDeception-Framework) - Source code and framework
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## Usage
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author={Wu, Yichen and Gao, Qianqian and Pan, Xudong and Hong, Geng and Yang, Min},
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journal={arXiv preprint arXiv:},
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year={2026},
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url={https://arxiv.org/abs/2504.13707v3}
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}
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```
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## Details
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For more information, visit the [GitHub repository](https://github.com/Simoniracle/OpenDeception-Framework) or read the [paper](https://arxiv.org/abs/2504.13707v3).
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### Framework versions
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