| --- |
| |
| language: |
| - en |
| tags: |
| - coreference-resolution |
| - maverick |
| - efficient |
| - accurate |
| license: |
| - cc-by-nc-sa-4.0 |
| datasets: |
| - OntoNotes |
| metrics: |
| - CoNLL |
| task_categories: |
| - coreference-resolution |
| model-index: |
| - name: sapienzanlp/maverick-mes-ontonotes |
| results: |
| - task: |
| type: coreference-resolution |
| name: coreference-resolution |
| dataset: |
| name: ontonotes |
| type: coreference |
| metrics: |
| - name: Avg. F1 |
| type: CoNLL |
| value: 83.6 |
|
|
| --- |
| # Maverick mes OntoNotes |
| Official weights for *Maverick-mes* trained on OntoNotes and based on DeBERTa-large. |
| This model achieves 83.6 Avg CoNLL-F1 on OntoNotes. |
|
|
| Other available models at [SapienzaNLP huggingface hub](https://huggingface.co/collections/sapienzanlp/maverick-coreference-resolution-66a750a50246fad8d9c7086a): |
|
|
| | hf_model_name | training dataset | Score | Singletons | |
| |:-----------------------------------:|:----------------:|:-----:|:----------:| |
| | ["sapienzanlp/maverick-mes-ontonotes"](https://huggingface.co/sapienzanlp/maverick-mes-ontonotes) | OntoNotes | 83.6 | No | |
| | ["sapienzanlp/maverick-mes-litbank"](https://huggingface.co/sapienzanlp/maverick-mes-litbank) | LitBank | 78.0 | Yes | |
| | ["sapienzanlp/maverick-mes-preco"](https://huggingface.co/sapienzanlp/maverick-mes-preco) | PreCo | 87.4 | Yes | |
| <!-- | ["sapienzanlp/maverick-s2e-ontonotes"](https://huggingface.co/sapienzanlp/maverick-mes-preco) | OntoNotes | 83.4 | No | No | --> |
| <!-- | "sapienzanlp/maverick-incr-ontonotes" | Ontonotes | 83.5 | No | No | --> |
| <!-- | "sapienzanlp/maverick-mes-ontonotes-base" | Ontonotes | 81.4 | No | No | --> |
| <!-- | "sapienzanlp/maverick-s2e-ontonotes-base" | Ontonotes | 81.1 | No | No | --> |
| <!-- | "sapienzanlp/maverick-incr-ontonotes-base" | Ontonotes | 81.0 | No | No | --> |
| <!-- | "sapienzanlp/maverick-s2e-litbank" | LitBank | 77.6 | Yes | No | --> |
| <!-- | "sapienzanlp/maverick-incr-litbank" | LitBank | 78.3 | Yes | No | --> |
| <!-- | "sapienzanlp/maverick-s2e-preco" | PreCo | 87.2 | Yes | No | --> |
| <!-- | "sapienzanlp/maverick-incr-preco" | PreCo | 88.0 | Yes | No | --> |
| N.B. Each dataset has different annotation guidelines, choose your model according to your use case. |
|
|
| ### Results on OntoNotes |
| <img src="https://cdn-uploads.huggingface.co/production/uploads/65e9ccd84ce78d665a50f78b/-5Wi_xL2o-71uQcl3d8B9.png" alt="drawing" width="95%"/> |
|
|
| ## Maverick: Efficient and Accurate Coreference Resolution Defying recent trends |
|
|
| [](https://arxiv.org/pdf/2407.21489) |
| [](https://creativecommons.org/licenses/by-nc/4.0/) |
| [](https://pypi.org/project/maverick-coref/) |
| [](https://github.com/SapienzaNLP/maverick-coref) |
|
|
| ### Citation |
|
|
| ``` |
| @inproceedings{martinelli-etal-2024-maverick, |
| title = "Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends", |
| author = "Martinelli, Giuliano and |
| Barba, Edoardo and |
| Navigli, Roberto", |
| booktitle = "Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2024)", |
| year = "2024", |
| address = "Bangkok, Thailand", |
| publisher = "Association for Computational Linguistics", |
| } |
| ``` |