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@@ -26,7 +26,7 @@ TrustNet is trained through contrastive learning to improve upon the base Qwen2.
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  - The User Trust Score is a continuous value in [0,1], where values near 1 indicate strong trust in AI, values near 0 indicate pronounced skepticism, and intermediate values (e.g., 0.5) represent a neutral or ambiguous stance.
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  ## Links
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- - [Paper](https://arxiv.org/abs/2504.13707) - arXiv:2504.13707
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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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  - The User Trust Score is a continuous value in [0,1], where values near 1 indicate strong trust in AI, values near 0 indicate pronounced skepticism, and intermediate values (e.g., 0.5) represent a neutral or ambiguous stance.
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  ## Links
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+ - [Paper](https://arxiv.org/abs/2504.13707) - arXiv:2504.13707[v3]
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  - [GitHub Repository](https://github.com/Simoniracle/OpenDeception-Framework) - Source code and framework
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  ## Usage