Update README.md

README.md

@@ -30,7 +30,35 @@ dataset_info:
     num_examples: 22948
   download_size: 50953604
   dataset_size: 73937561
+license: cc-by-sa-4.0
+task_categories:
+- text2text-generation
+language:
+- en
+- ja
+pretty_name: Simplifyingmt
 ---
-# Dataset Card for "Simplifyingmt"
+## SimplifyingMT
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Dataset Description
+-Repository: [https://github.com/nttcslab-nlp/SimplifyingMT_ACL24](https://github.com/nttcslab-nlp/SimplifyingMT_ACL24)  
+-Papre: to appear
+
+## Paper
+
+Oshika et al., Simplifying Translations for Children: Iterative Simplification Considering Age of Acquisition with LLMs, Findings of ACL 2024
+
+## Abstract
+
+In recent years, neural machine translation (NMT) has been widely used in everyday life.
+However, the current NMT lacks a mechanism to adjust the difficulty level of translations to match the user's language level.
+Additionally, due to the bias in the training data for NMT, translations of simple source sentences are often produced with complex words.
+In particular, this could pose a problem for children, who may not be able to understand the meaning of the translations correctly. 
+In this study, we propose a method that replaces words with high Age of Acquisitions (AoA) in translations with simpler words to match the translations to the user's level.
+We achieve this by using large language models (LLMs), providing a triple of a source sentence, a translation, and a target word to be replaced.
+We create a benchmark dataset using back-translation on Simple English Wikipedia.
+The experimental results obtained from the dataset show that our method effectively replaces high-AoA words with lower-AoA words and, moreover, can iteratively replace most of the high-AoA words while still maintaining high BLEU and COMET scores.
+
+## License
+Simple-English-Wikipedia is distributed under the CC-BY-SA 4.0 license.  
+This dataset follows suit and is distributed under the CC-BY-SA 4.0 license.