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@@ -6,7 +6,7 @@ language:
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  - en
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  pipeline_tag: sentence-similarity
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  ---
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- ## Model to score relative persuasive language between pairs
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  More info about training, evaluation, and use in paper is here: https://arxiv.org/abs/2406.17753
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  Python:
@@ -29,4 +29,19 @@ def predict(textA, textB, model,tokenizer):
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  score2=logits.detach().cpu().numpy()*(-1)
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  score = (score1+score2)/2
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  return score
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  - en
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  pipeline_tag: sentence-similarity
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  ---
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+ # Model to score relative persuasive language between pairs
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  More info about training, evaluation, and use in paper is here: https://arxiv.org/abs/2406.17753
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  Python:
 
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  score2=logits.detach().cpu().numpy()*(-1)
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  score = (score1+score2)/2
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  return score
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+ ```
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+
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+ ## Citation
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+
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+ If you find our dataset helpful, kindly refer to us in your work using the following citation:
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+ ```
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+ @misc{pauli2024measuringbenchmarkinglargelanguage,
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+ title={Measuring and Benchmarking Large Language Models' Capabilities to Generate Persuasive Language},
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+ author={Amalie Brogaard Pauli and Isabelle Augenstein and Ira Assent},
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+ year={2024},
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+ eprint={2406.17753},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2406.17753},
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+ }
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  ```