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  license: mit
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  language:
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  - en
 
 
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  ---
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  # NegMPNet
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  This is a negation-aware version of [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2).
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- It is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
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  <!--- Describe your model here -->
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  )
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  ```
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- ## Citing & Authors
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-
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- If you use our model, please cite our INLG 2023 paper:
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- tba
 
 
 
 
 
 
 
 
 
 
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  license: mit
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  language:
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  - en
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+ datasets:
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+ - tum-nlp/cannot-dataset
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  ---
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  # NegMPNet
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  This is a negation-aware version of [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2).
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+ It is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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+ For further information, see our paper [This is not correct! Negation-aware Evaluation of Language Generation Systems](https://arxiv.org/abs/2307.13989).
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  <!--- Describe your model here -->
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  )
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  ```
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+ ## Citation
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+ Please cite our [INLG 2023 paper](https://arxiv.org/abs/2307.13989), if you use our model.
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+ **BibTeX:**
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+ ```bibtex
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+ @misc{anschütz2023correct,
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+ title={This is not correct! Negation-aware Evaluation of Language Generation Systems},
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+ author={Miriam Anschütz and Diego Miguel Lozano and Georg Groh},
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+ year={2023},
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+ eprint={2307.13989},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+ ```