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README.md
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@@ -53,7 +53,7 @@ Other available models at [SapienzaNLP huggingface hub](https://huggingface.co/c
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N.B. Each dataset has different annotation guidelines, choose your model according to your use case.
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### Results on OntoNotes
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<img src="https://cdn-uploads.huggingface.co/production/uploads/65e9ccd84ce78d665a50f78b/-5Wi_xL2o-71uQcl3d8B9.png" alt="drawing" width="
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## Maverick: Efficient and Accurate Coreference Resolution Defying recent trends
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address = "Bangkok, Thailand",
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publisher = "Association for Computational Linguistics",
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}
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```
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[F-coref: Fast, Accurate and Easy to Use Coreference Resolution](https://aclanthology.org/2022.aacl-demo.6) (Otmazgin et al., AACL-IJCNLP 2022)
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N.B. Each dataset has different annotation guidelines, choose your model according to your use case.
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### Results on OntoNotes
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<img src="https://cdn-uploads.huggingface.co/production/uploads/65e9ccd84ce78d665a50f78b/-5Wi_xL2o-71uQcl3d8B9.png" alt="drawing" width="95%"/>
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## Maverick: Efficient and Accurate Coreference Resolution Defying recent trends
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address = "Bangkok, Thailand",
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publisher = "Association for Computational Linguistics",
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}
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```
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