Update README.md

README.md

@@ -1,3 +1,117 @@
 ---
 license: cc-by-nc-4.0
+task_categories:
+- text-generation
+language:
+- en
+- de
+- ar
+- ja
+- ko
+- es
+- zh
+pretty_name: medit
+size_categories:
+- 10K<n<100K
 ---
+# Dataset Card for mEdIT: Multilingual Text Editing via Instruction Tuning
+
+## Paper: [mEdIT: Multilingual Text Editing via Instruction Tuning](https://arxiv.org/abs/2402.16472)
+## Authors: Vipul Raheja, Dimitris Alikaniotis, Vivek Kulkarni, Bashar Alhafni, Dhruv Kumar
+## Project Repo: [https://github.com/vipulraheja/medit](https://github.com/vipulraheja/medit)
+
+
+## Dataset Summary
+This is the dataset that was used to train the mEdIT text editing models. Full details of the dataset can be found in our paper.
+
+
+# Dataset Structure
+The dataset is in JSON format. 
+
+## Data Instances
+```
+{
+  "instance":867453,
+  "task":"gec",
+  "language":"english",
+  "lang":"en",
+  "dataset":"lang8.bea19",
+  "src":"Fix grammar in this sentence: Luckily there was no damage for the earthquake .",
+  "prompt":"### 命令:\nこの文の文法上の誤りを修正してください\n### 入力:\nLuckily there was no damage for the earthquake .\n### 出力:\n\n",
+  "text":"Luckily there was no damage from the earthquake two years ago ."
+}
+```
+
+## Data Fields
+* `instance`: instance ID
+* `language`: Language of input and edited text 
+* `lang`: Language code in ISO-639-1
+* `dataset`: Source of the current example
+* `task`: Text editing task for this instance
+* `src`: input text (formatted as `instruction: input_text`)
+* `prompt`: Full prompt (instruction + input) for training the models
+* `text`: output text
+
+
+## Considerations for Using the Data
+Please note that this dataset contains 69k instances (as opposed to the 190k instances we used in the paper). 
+This is because this public release includes only the instances that were acquired and curated from publicly available datasets. 
+Specifically, it is missing roughly 13k instances in training and 1.5k instances in validation data from Simplification and Formality Transfer tasks due to licensing restrictions.
+
+Following are the details of the subsets (including the ones we are unable to publicly release):
+
+*Grammatical Error Correction*:
+- English:
+  - FCE, Lang8, and W&I+LOCNESS data can be found at: https://www.cl.cam.ac.uk/research/nl/bea2019st/#data
+  - *Note* that we are unable to share Lang8 data due to license restrictions
+- Arabic:
+  - The QALB-2014 and QALB-2015 datasets can be requested at: https://docs.google.com/forms/d/e/1FAIpQLScSsuAu1_84KORcpzOKTid0nUMQDZNQKKnVcMilaIZ6QF-xdw/viewform
+  - *Note* that we are unable to share them due to license restrictions
+  - ZAEBUC: Can be requested at https://docs.google.com/forms/d/e/1FAIpQLSd0mFkEA6SIreDyqQXknwQrGOhdkC9Uweszgkp73gzCErEmJg/viewform
+- Chinese:
+  - NLPCC-2018 data can be found at: https://github.com/zhaoyyoo/NLPCC2018_GEC
+- German:
+  - FalKO-MERLIN GEC Corpus can be found at: https://github.com/adrianeboyd/boyd-wnut2018?tab=readme-ov-file#download-data
+- Spanish:
+  - COWS-L2H dataset can be found at: https://github.com/ucdaviscl/cowsl2h
+- Japanese:
+  - NAIST Lang8 Corpora can be found at: https://sites.google.com/site/naistlang8corpora
+  - *Note* that we are unable to share this data due to license restrictions
+- Korean:
+  - Korean GEC data can be found at: https://github.com/soyoung97/Standard_Korean_GEC
+  - *Note* that we are unable to share this data due to license restrictions
+
+*Simplification*:
+- English:
+  - WikiAuto dataset can be found at: https://huggingface.co/datasets/wiki_auto
+  - WikiLarge dataset can be found at: https://github.com/XingxingZhang/dress
+  - *Note* that we are unable to share Newsela data due to license restrictions.
+- Arabic, Spanish, Korean, Chinese:
+  - *Note* that we are unable to share the translated Newsela data due to license restrictions.
+- German:
+  - GeoLino dataset can be found at: http://www.github.com/Jmallins/ZEST.
+  - TextComplexityDE dataset can be found at: https://github.com/babaknaderi/TextComplexityDE
+- Japanese:
+  - EasyJapanese and EasyJapaneseExtended datasets were taken from the MultiSim dataset: https://huggingface.co/datasets/MichaelR207/MultiSim/tree/main/data/Japanese
+
+
+*Paraphrasing*: 
+- Arabic: 
+  - NSURL-19 (Shared Task 8) data can be found at: https://www.kaggle.com/competitions/nsurl-2019-task8
+  - *Note* that we are unable to share the NSURL data due to license restrictions.
+- English, Chinese, German, Japanese, Korean, Spanish:
+  - PAWS-X data can be found at: https://huggingface.co/datasets/paws-x
+ 
+
+## Citation 
+
+```
+@misc{raheja2024medit,
+      title={mEdIT: Multilingual Text Editing via Instruction Tuning}, 
+      author={Vipul Raheja and Dimitris Alikaniotis and Vivek Kulkarni and Bashar Alhafni and Dhruv Kumar},
+      year={2024},
+      eprint={2402.16472},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```