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@@ -26,7 +26,9 @@ This repository contains information about Russian Paradetox dataset -- the firs
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  ## ParaDetox Collection Pipeline
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- The ParaDetox Dataset collection was done via [Yandex.Toloka](https://toloka.yandex.com/) crowdsource platform. The collection was done in three steps:
 
 
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  * *Task 1:* **Generation of Paraphrases**: The first crowdsourcing task asks users to eliminate toxicity in a given sentence while keeping the content.
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  * *Task 2:* **Content Preservation Check**: We show users the generated paraphrases along with their original variants and ask them to indicate if they have close meanings.
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  * *Task 3:* **Toxicity Check**: Finally, we check if the workers succeeded in removing toxicity.
@@ -36,14 +38,19 @@ All these steps were done to ensure high quality of the data and make the proces
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  ## Detoxification model
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  The first *seqseq* SOTA for the detoxification task in Russian -- ruT5 (base) model fine-tuned on the Russian ParaDetox dataset -- we released online in HuggingFace🤗 repository [here](https://huggingface.co/s-nlp/ruT5-base-detox).
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- You can also check out our [demo](https://detoxifier.nlp.zhores.net/junction/) and telegram [bot](https://t.me/rudetoxifierbot).
 
 
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  ## Citation
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  ```
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- @article{dementievarusse,
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- title={RUSSE-2022: Findings of the First Russian Detoxification Shared Task Based on Parallel Corpora},
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- author={Dementieva, Daryna and Logacheva, Varvara and Nikishina, Irina and Fenogenova, Alena and Dale, David and Krotova, Irina and Semenov, Nikita and Shavrina, Tatiana and Panchenko, Alexander}
 
 
 
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  }
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  ```
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  and
 
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  ## ParaDetox Collection Pipeline
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+ <img alt="Collection Pipeline" src="generation_pipeline_blue-1.png">
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+
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+ The ParaDetox Dataset collection was done via [Toloka.ai](https://toloka.ai) crowdsource platform. The collection was done in three steps:
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  * *Task 1:* **Generation of Paraphrases**: The first crowdsourcing task asks users to eliminate toxicity in a given sentence while keeping the content.
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  * *Task 2:* **Content Preservation Check**: We show users the generated paraphrases along with their original variants and ask them to indicate if they have close meanings.
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  * *Task 3:* **Toxicity Check**: Finally, we check if the workers succeeded in removing toxicity.
 
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  ## Detoxification model
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  The first *seqseq* SOTA for the detoxification task in Russian -- ruT5 (base) model fine-tuned on the Russian ParaDetox dataset -- we released online in HuggingFace🤗 repository [here](https://huggingface.co/s-nlp/ruT5-base-detox).
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+ Also, we release the toxicity classifier 🤗[here](https://huggingface.co/s-nlp/russian_toxicity_classifier)
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+
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+ [Old Versions] You can also check out our [demo](https://detoxifier.nlp.zhores.net/junction/) and telegram [bot](https://t.me/rudetoxifierbot).
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  ## Citation
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  ```
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+ @article{Dementieva2022RUSSE2022FO,
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+ title = {{RUSSE-2022: Findings of the First Russian Detoxification Shared Task Based on Parallel Corpora}},
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+ author = {Daryna Dementieva and Varvara Logacheva and Irina Nikishina and Alena Fenogenova and David Dale and I. Krotova and Nikita Semenov and Tatiana Shavrina and Alexander Panchenko},
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+ year = 2022,
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+ journal = {COMPUTATIONAL LINGUISTICS AND INTELLECTUAL TECHNOLOGIES},
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+ url = {https://api.semanticscholar.org/CorpusID:253169495}
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  }
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  ```
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  and