update README to v2

README.md

@@ -20,8 +20,16 @@ configs:  # Optional. This can be used to pass additional parameters to the data
 
 # Dataset Card for LuxAlign
 
+## ⚠️ Update
+We have updated the original dataset ([fredxlpy/LuxAlign_v1](https://huggingface.co/datasets/fredxlpy/LuxAlign_v1)) with the following improvements:
+- **Data Coverage**: Extended to news articles published up to **2nd December 2024** ((previously May 10, 2024)).
+- **Data Cleaning**: HTML tags that were previously undetected have now been removed.
+- **Sentence Splitting**: Improved sentence tokenizer performance to fix previously incorrect splits.
+- **Placeholder Tags**: Replaced phone numbers, email addresses, and URLs with `[phone]`, `[email]`, and `[url]` tags using regex patterns.
+
+
 ## Dataset Summary
-LuxAlign is a parallel dataset featuring Luxembourgish-English and Luxembourgish-French sentence pairs, introduced in [*LuxEmbedder: A Cross-Lingual Approach to Enhanced Luxembourgish Sentence Embeddings (Philippy et al., 2024)*](#). Designed to align the Luxembourgish embedding space with those of other languages, it enables improved cross-lingual sentence representations for Luxemborgish. This dataset was used to train the Luxembourgish sentence embedding model [**LuxEmbedder**](https://huggingface.co/fredxlpy/LuxEmbedder). The data originates from news articles published by the Luxembourgish news platform [RTL.lu](https://www.rtl.lu).
+LuxAlign is a parallel dataset featuring Luxembourgish-English and Luxembourgish-French sentence pairs, introduced in [*LuxEmbedder: A Cross-Lingual Approach to Enhanced Luxembourgish Sentence Embeddings (Philippy et al., 2024)*](https://doi.org/10.48550/arXiv.2412.03331). Designed to align the Luxembourgish embedding space with those of other languages, it enables improved cross-lingual sentence representations for Luxemborgish. This dataset was used to train the Luxembourgish sentence embedding model [**LuxEmbedder**](https://huggingface.co/fredxlpy/LuxEmbedder). The data originates from news articles published by the Luxembourgish news platform [RTL.lu](https://www.rtl.lu).
 
 The sentence pairs in this dataset are not always exact translations but instead reflect high semantic similarity; hence, this dataset may not be suitable for training a machine translation model without caution.