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 **NEWS:** 
-1) [AfriCOMET](https://arxiv.org/pdf/2311.09828.pdf) released, a new model to embrace under-resourced African Languages.
-2) We released our new eXplainable COMET models ([XCOMET-XL](https://huggingface.co/Unbabel/XCOMET-XL) and [-XXL](https://huggingface.co/Unbabel/XCOMET-XXL)) which along with quality scores detects which errors in the translation are minor, major or critical according to MQM typology
-3) We release [CometKiwi -XL (3.5B)](https://huggingface.co/Unbabel/wmt23-cometkiwi-da-xl) and [-XXL (10.7B)](https://huggingface.co/Unbabel/wmt23-cometkiwi-da-xxl) QE models. These models were the best performing QE models on the WMT23 QE shared task.
-4) We now support [DocCOMET](https://statmt.org/wmt22/pdf/2022.wmt-1.6.pdf), a document-level extension of COMET which can utilize contextual information. Using context improves accuracy on discourse phenomena tasks as well as referenceless evaluation of [chat translation quality](https://arxiv.org/pdf/2403.08314).
+1) We added a new method to extract free-text explanations from XCOMET outputs! [Check this section](https://github.com/Unbabel/COMET?tab=readme-ov-file#explaining-translation-errors)
+2) We now support [DocCOMET](https://statmt.org/wmt22/pdf/2022.wmt-1.6.pdf), a document-level extension of COMET which can utilize contextual information. Using context improves accuracy on discourse phenomena tasks as well as referenceless evaluation of [chat translation quality](https://arxiv.org/pdf/2403.08314).
+3) We released our new eXplainable COMET models ([XCOMET-XL](https://huggingface.co/Unbabel/XCOMET-XL) and [-XXL](https://huggingface.co/Unbabel/XCOMET-XXL)) which along with quality scores detects which errors in the translation are minor, major or critical according to MQM typology
 
 Please check all available models [here](https://github.com/Unbabel/COMET/blob/master/MODELS.md)