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@@ -17,13 +17,13 @@ Yibo Hu, MohammadSaleh Hosseini, Erick Skorupa Parolin, Javier Osorio, Latifur K
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  2022, NAACL 2022 conference
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  ## Repository
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- [GitHub Repository](https://github.com/snowood1/ConfliBERT)
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  ## Paper
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- [ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence](https://aclanthology.org/2022.naacl-main.395/)
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  ## Model Description
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- ConfliBERT is a transformer model pretrained on a vast corpus of texts related to political conflict and violence. This model is based on the BERT architecture and is specialized for analyzing texts within its domain, using masked language modeling (MLM) and next sentence prediction (NSP) as its main pretraining objectives. It is designed to improve performance in tasks like sentiment analysis, event extraction, and entity recognition for texts dealing with political subjects.
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  ## Model Variants
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  ConfliBERT has several variants, each fine-tuned on specific datasets to cater to different use cases within the domain of political conflict and violence:
@@ -73,10 +73,9 @@ ConfliBERT has shown improved performance on several benchmarks relevant to its
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  If you use ConfliBERT in your research, please cite the following paper:
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  ```bibtex
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  @inproceedings{hu2022conflibert,
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- title={ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence},
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- author={Hu, Yibo and Hosseini, MohammadSaleh and Parolin, Erick Skorupa and Osorio, Javier and Khan, Latifur and Brandt, Patrick and D’Orazio, Vito},
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- booktitle={Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
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- pages={5469--5482},
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- year={2022}
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  }
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  ```
 
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  2022, NAACL 2022 conference
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  ## Repository
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+ [GitHub Repository](https://github.com/eventdata/ConfliBERT)
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  ## Paper
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+ [ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence](https://aclanthology.org/2022.naacl-main.400/)
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  ## Model Description
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+ ConfliBERT is a transformer model pretrained on a vast corpus of texts related to political conflict and violence. This model is based on the BERT architecture and is specialized for analyzing texts within its domain, using masked language modeling (MLM) and next sentence prediction (NSP) as its main pretraining objectives. It is designed to improve performance in tasks like event extraction, and entity recognition for texts dealing with political subjects.
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  ## Model Variants
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  ConfliBERT has several variants, each fine-tuned on specific datasets to cater to different use cases within the domain of political conflict and violence:
 
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  If you use ConfliBERT in your research, please cite the following paper:
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  ```bibtex
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  @inproceedings{hu2022conflibert,
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+ title={Conflibert: A pre-trained language model for political conflict and violence},
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+ author={Hu, Yibo and Hosseini, MohammadSaleh and Skorupa Parolin, Erick and Osorio, Javier and Khan, Latifur and Brandt, Patrick and D’Orazio, Vito},
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+ year={2022},
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+ organization={Association for Computational Linguistics}
 
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  }
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  ```