Update README.md

README.md

@@ -2,6 +2,11 @@
 license: cc-by-4.0
 task_categories:
 - summarization
+- text-generation
+annotations_creators:
+  - found
+language_creators:
+  - found
 language:
 - am
 - az
@@ -45,6 +50,10 @@ language:
 pretty_name: LR-Sum
 size_categories:
 - 100K<n<1M
+multilinguality:
+  - multilingual
+tags:
+  - conditional-text-generation
 viewer: false
 ---
 # Dataset Card for LR-Sum
@@ -57,39 +66,37 @@ This dataset card aims to be a base template for new datasets. It has been gener
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
+LR-Sum is a permissively-licensed dataset created with the goal of enabling further research in automatic summarization for less-resourced languages.
+LR-Sum contains human-written summaries for 40 languages, many of which are less-resourced. 
+The data is based on the collection of the Multilingual Open Text corpus where the source data is public domain newswire collected from from Voice of America websites.
+LR-Sum is released under a Creative Commons license (CC BY 4.0), making it one of the most openly-licensed multilingual summarization datasets. 
 
-
-
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+- **Curated by:** BLT Lab: Chester Palen-Michel and Constantine Lignos
+- **Shared by:** Chester Palen-Michel
+- **Language(s) (NLP): Albanian, Amharic, Armenian, Azerbaijani, Bengali, Bosnian, Burmese, Chinese, English, French, Georgian, Greek, Haitian Creole, Hausa, Indonesian, Khmer, Kinyarwanda, Korean, Kurdish, Lao, Macedonian, Northern Ndebele, Pashto, Persian, Portuguese, Russian, Serbian, Shona, Somali, Spanish, Swahili, Thai, Tibetan, Tigrinya, Turkish, Ukrainian, Urdu, Uzbek, Vietnamese
+- **License:** CC-BY 4.0
 
 ### Dataset Sources [optional]
 
-<!-- Provide the basic links for the dataset. -->
+Multilingual Open Text v1.6
+which is a collection of newswire text from Voice of America (VOA).
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** https://github.com/bltlab/lr-sum
+- **Paper:** https://aclanthology.org/2023.findings-acl.427/
 
 ## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
+The dataset is intended for research in automatic summarization in various languages, especially for less resourced languages.
 
 ### Direct Use
 
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
+The data can be used for training text generation models to generate short summaries of news articles in many languages.
+Automatic evaluation of automatic summarization is another use case, though we encourage also conducting human evaluation of any model trained for summarization.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+This dataset only includes newswire text, so models trained on the data may not be effective for out of domain summarization. 
 
-[More Information Needed]
 
 ## Dataset Structure
 
@@ -155,32 +162,37 @@ This dataset card aims to be a base template for new datasets. It has been gener
 
 Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
 
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+## Citation
 
 **BibTeX:**
-
-[More Information Needed]
+```
+@inproceedings{palen-michel-lignos-2023-lr,
+    title = "{LR}-Sum: Summarization for Less-Resourced Languages",
+    author = "Palen-Michel, Chester  and
+      Lignos, Constantine",
+    editor = "Rogers, Anna  and
+      Boyd-Graber, Jordan  and
+      Okazaki, Naoaki",
+    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
+    month = jul,
+    year = "2023",
+    address = "Toronto, Canada",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2023.findings-acl.427",
+    doi = "10.18653/v1/2023.findings-acl.427",
+    pages = "6829--6844",
+    abstract = "We introduce LR-Sum, a new permissively-licensed dataset created with the goal of enabling further research in automatic summarization for less-resourced languages.LR-Sum contains human-written summaries for 40 languages, many of which are less-resourced. We describe our process for extracting and filtering the dataset from the Multilingual Open Text corpus (Palen-Michel et al., 2022).The source data is public domain newswire collected from from Voice of America websites, and LR-Sum is released under a Creative Commons license (CC BY 4.0), making it one of the most openly-licensed multilingual summarization datasets. We describe abstractive and extractive summarization experiments to establish baselines and discuss the limitations of this dataset.",
+}
+```
 
 **APA:**
 
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
+Palen-Michel, C. & Lignos, C. (2023). LR-Sum: Summarization for Less-Resourced Languages. In Findings of the Association for Computational Linguistics: ACL 2023, pages 6829–6844, Toronto, Canada. Association for Computational Linguistics.
 
 ## Dataset Card Authors [optional]
 
-[More Information Needed]
+Chester Palen-Michel
 
 ## Dataset Card Contact
 
-[More Information Needed]
+Chester Palen-Michel