Update README.md

README.md

@@ -9,6 +9,11 @@ language:
 - ar
 - hi
 - es
+- it
+- fr
+- he
+- ja
+- tt
 license: openrail++
 size_categories:
 - 1K<n<10K
@@ -72,7 +77,7 @@ configs:
   - split: hi
     path: data/hi-*
 ---
-**MultiParaDetox**
+**Multilingual Text Detoxification with Parallel Data**
 
 [![COLING2025](https://img.shields.io/badge/COLING%202025-b31b1b)](https://aclanthology.org/2025.coling-main.535/) 
 [![CLEF2024](https://img.shields.io/badge/CLEF%202024-b31b1b)](https://ceur-ws.org/Vol-3740/paper-223.pdf) 
@@ -82,11 +87,15 @@ For each of 9 languages, we collected 1k pairs of toxic<->detoxified instances s
 
 📰 **Updates**
 
+**[2025]** The second edition of TextDetox shared task! [webpage](https://pan.webis.de/clef25/pan25-web/text-detoxification.html)
+
+**[2025]** We extend our data to new languages! Now also included: Italian, French, Hebrew, Hinglish, Japanese, Tatar. Check our [test](https://huggingface.co/datasets/textdetox/multilingual_paradetox_test) part.
+
 **[2025]** We dived into the explainability of our data in our new [COLING paper](https://huggingface.co/papers/2412.11691)!
 
 **[2024]** You can check additional releases for [Ukrainian ParaDetox](https://huggingface.co/datasets/textdetox/uk_paradetox) and [Spanish ParaDetox](https://huggingface.co/datasets/textdetox/es_paradetox) from NAACL 2024!
 
-**[2024]** **April, 23rd, update: We are realsing the parallel dev set! The test part for the final phase of the competition is available [here](https://huggingface.co/datasets/textdetox/multilingual_paradetox_test)!!!**
+**[2024]** **April, 23rd, update: We are realsing the parallel train set! The test part for the final phase of the competition is available [here](https://huggingface.co/datasets/textdetox/multilingual_paradetox_test)!!!**
 
 **[2022]** You can also check previously created training corpora: [English ParaDetox](https://huggingface.co/datasets/s-nlp/paradetox) from ACL 2022 and [Russian ParaDetox](https://huggingface.co/datasets/s-nlp/ru_paradetox).
 
@@ -101,6 +110,12 @@ The list of the sources for the original toxic sentences:
 * Amhairc: [Amharic Hate Speech](https://github.com/uhh-lt/AmharicHateSpeech)
 * Arabic: [OSACT4](https://edinburghnlp.inf.ed.ac.uk/workshops/OSACT4/)
 * Hindi: [Hostility Detection Dataset in Hindi](https://competitions.codalab.org/competitions/26654#learn_the_details-dataset), [Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages](https://dl.acm.org/doi/pdf/10.1145/3368567.3368584?download=true)
+* Italian: [AMI](https://github.com/dnozza/ami2020), [HODI](https://github.com/HODI-EVALITA/HODI_2023), [Jigsaw Multilingual Toxic Comment](https://www.kaggle.com/competitions/jigsaw-multilingual-toxic-comment-classification/overview)
+* French: [FrenchToxicityPrompts](https://europe.naverlabs.com/research/publications/frenchtoxicityprompts-a-large-benchmark-for-evaluating-and-mitigating-toxicity-in-french-texts/), [Jigsaw Multilingual Toxic Comment](https://www.kaggle.com/competitions/jigsaw-multilingual-toxic-comment-classification/overview)
+* Hebrew: [Hebrew Offensive Language Dataset](https://github.com/NataliaVanetik/HebrewOffensiveLanguageDatasetForTheDetoxificationProject/tree/main)
+* Hinglish: [Hinglish Hate Detection](https://github.com/victor7246/Hinglish_Hate_Detection/blob/main/data/raw/trac1-dataset/hindi/agr_hi_dev.csv)
+* Japanese: posts from [2chan](https://huggingface.co/datasets/p1atdev/open2ch)
+* Tatar: ours.
 
 ## Citation
 If you would like to acknowledge our work, please, cite the following manuscripts: