Datasets:

cis-lmu
/

udhr-lid

@@ -468,7 +468,8 @@ For dealing with scripts in other languages, if you are interested, check Glotsc
 We believe UDHR should remain a test corpus in NLP, not a training corpus. Of course, we are not opposed to great works such as Franc built on top of UDHR. However, if your work scale is much bigger than UDHR, do not put UDHR in your data. Use it as test/validation, or find out what is wrong with your training data with help of UDHR. Be aware that a part of UDHR may be hosted on other websites such as Wikipedia, news websites like BBC, collaborative translation communities like Tatoeba. Before using UDHR as a test, exclude any sentence where UDHR is a part of your training.
-We created this corpus for language identification evaluation task, but feel free to use it for your own task. The texts here are not in order, and they're not parallel. However, each row of data belongs to the determined language, long, cleaned, and has rich linguistic content!
 ## Usage (HF Loader)

 We believe UDHR should remain a test corpus in NLP, not a training corpus. Of course, we are not opposed to great works such as Franc built on top of UDHR. However, if your work scale is much bigger than UDHR, do not put UDHR in your data. Use it as test/validation, or find out what is wrong with your training data with help of UDHR. Be aware that a part of UDHR may be hosted on other websites such as Wikipedia, news websites like BBC, collaborative translation communities like Tatoeba. Before using UDHR as a test, exclude any sentence where UDHR is a part of your training.
+We created this corpus for language identification evaluation task in our GlotLID [paper](https://arxiv.org/abs/2310.16248), but feel free to use it for your own task. The texts here are not in order, and they're not parallel. However, each row of data belongs to the determined language, long, cleaned, and has rich linguistic content!
 ## Usage (HF Loader)