Add link to paper

This PR adds a link to the paper associated with this dataset: https://huggingface.co/papers/2502.11187

README.md

@@ -1,8 +1,10 @@
 ---
-task_categories:
-- text-generation
 language:
 - bn
+license: cc-by-4.0
+task_categories:
+- text-generation
+pretty_name: TituLM Bangla Corpus
 dataset_info:
 - config_name: common_crawl
   features:
@@ -44,7 +46,7 @@ configs:
 - config_name: default
   data_files:
   - split: train
-    path: "**/train-*.parquet"
+    path: '**/train-*.parquet'
 - config_name: common_crawl
   data_files:
   - split: train
@@ -57,11 +59,12 @@ configs:
   data_files:
   - split: train
     path: translated/train-*
-license: cc-by-4.0
-pretty_name: TituLM Bangla Corpus
 ---
 
 ## TituLM Bangla Corpus
+
+This dataset is associated with the paper [TituLLMs: A Family of Bangla LLMs with Comprehensive Benchmarking](https://huggingface.co/papers/2502.11187)
+
 **TituLM Bangla Corpus** is one of the largest Bangla clean corpus prepared for pretraining, continual pretraining or fine-tuning Large Language Model(LLM) for improving Bangla text generation capability.
 This dataset contains diverse sources and categories of Bangla text. The largest part of this dataset contains filtered common crawled datasets. As we saw existing all common crawl datasets have issues with proper text extraction from HTML pages and Bangla language specific filtering as all those datasets build for multilingual purposes.
 Keeping that in mind we applied [Trafilatura](https://trafilatura.readthedocs.io/en/latest/) tool to extract text from common crawl web pages. Compared to existing extraction pages we found this tool perform better. We generate several Bangla language specific quality signals over the dataset and filtered using different quality signals threshold.