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  licenses:
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  - cc-by-nc-sa
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  licenses:
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  - cc-by-nc-sa
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+ ---
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+
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+ Mutual implication score: a symmetric measure of text semantic similarity
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+ based on a RoBERTA model pretrained for natural language inference
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+ and fine-tuned for paraphrase detection.
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+
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+ The following snippet illustrates code usage:
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+ ```python
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+ from mutual_implication_score import MIS
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+ mis = MIS(device='cpu')
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+ source_texts = ['I want to leave this room',
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+ 'Hello world, my name is Nick']
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+ paraphrases = ['I want to go out of this room',
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+ 'Hello world, my surname is Petrov']
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+ scores = mis.compute(source_texts, paraphrases)
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+ print(scores)
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+ # expected output: [0.9748, 0.0545]
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+ ```
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+
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+ The first two texts are semantically equivalent, their MIS is close to 1.
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+ The two other texts have different meanings, and their score is low.