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@@ -68,10 +68,13 @@ Microsoft => ORG
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  The **AITSecNER** model was fine-tuned using the [urchade/gliner_small](https://huggingface.co/urchade/gliner_small) model from Hugging Face on the [priamai/AnnoCTR dataset](https://huggingface.co/datasets/priamai/AnnoCTR). For more details about the dataset, see the paper ["AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports"](https://arxiv.org/abs/2305.10472).
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  ## About
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  **AITSecNER** leverages GLiNER to quickly and accurately extract cybersecurity-specific entities, making it highly suitable for tasks such as:
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  - Cyber threat intelligence analysis
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  - Incident response documentation
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- - Automated cybersecurity reporting
 
 
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  The **AITSecNER** model was fine-tuned using the [urchade/gliner_small](https://huggingface.co/urchade/gliner_small) model from Hugging Face on the [priamai/AnnoCTR dataset](https://huggingface.co/datasets/priamai/AnnoCTR). For more details about the dataset, see the paper ["AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports"](https://arxiv.org/abs/2305.10472).
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+ GLiNER is described in detail in the paper ["GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer"](https://arxiv.org/abs/2311.08526).
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  ## About
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  **AITSecNER** leverages GLiNER to quickly and accurately extract cybersecurity-specific entities, making it highly suitable for tasks such as:
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  - Cyber threat intelligence analysis
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  - Incident response documentation
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+ - Automated cybersecurity reporting
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+