readme updated

README.md

@@ -30,27 +30,28 @@ tags:
 
 # Historic Scripts to Modern Vision: Modi to Devanagari Transliteration Dataset
 
-This dataset supports research in the transliteration of **Modi script**—an ancient Indian script used historically in the Maharashtra region—into **Devanagari**, the script currently used for writing Marathi and several other Indian languages.
+This dataset supports research in the transliteration of **Modi script**—an ancient Indian script historically used in Maharashtra—into **Devanagari**, the script currently used for Marathi and several other Indian languages.
 
-The dataset was introduced in the paper:
+The dataset was introduced in the following paper:
 
 > **Historic Scripts to Modern Vision: A Novel Dataset and A VLM Framework for Transliteration of Modi Script to Devanagari**  
 > *Harshal Kausadikar, Tanvi Kale, Onkar Susladkar, Sparsh Mittal*  
-> arXiv preprint arXiv:2503.13060 (2025)
+> **Accepted at ICDAR 2025**  
+> [arXiv:2503.13060v2](https://arxiv.org/abs/2503.13060v2)
 
 ## Dataset Features
 
 - **Modi script image patches**
 - **Aligned Devanagari transliterations**
-- Multiple styles and variations of historical Modi handwriting
-- Ideal for tasks such as OCR, script transliteration, sequence learning, and multimodal VLM training
+- Covers a diverse range of historical Modi handwriting styles
+- Suitable for OCR, script transliteration, vision-language modeling, and low-resource script research
 
 ## Usage
 
-This dataset can be used for:
-- Script recognition and transliteration
-- Vision-language modeling for low-resource scripts
-- Historical document digitization
+This dataset is ideal for:
+- Handwritten script recognition and transliteration
+- Vision-language model (VLM) training for historical scripts
+- Document digitization and cultural heritage preservation
 
 ## Citation
 
@@ -62,4 +63,4 @@ If you use this dataset in your research or publications, **please cite the foll
   author={Kausadikar, Harshal and Kale, Tanvi and Susladkar, Onkar and Mittal, Sparsh},
   journal={arXiv preprint arXiv:2503.13060},
   year={2025}
-}
+}