Update README.md

README.md

@@ -13,20 +13,20 @@ task_ids: question-generation
 
 ## Dataset Description
 - **Repository:** [https://github.com/asahi417/lm-question-generation](https://github.com/asahi417/lm-question-generation)
-- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Paper:** [TBA](TBA)
 - **Point of Contact:** [Asahi Ushio](http://asahiushio.com/)
-- **Size of downloaded dataset files:** 284.1 MB
-- **Size of the generated dataset:** 269 MB
 
 ### Dataset Summary
-[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) dataset for question generation (QG) task. The split 
+This is a subset of [QG-Bench](https://github.com/asahi417/lm-question-generation/blob/master/QG_BENCH.md#datasets), a unified question generation benchmark proposed in
+ ["Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference"](paper_link).
+This is [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) dataset for question generation (QG) task. The split 
 of train/development/test set follows the ["Neural Question Generation"](https://arxiv.org/abs/1705.00106) work and is 
 compatible with the [leader board](https://paperswithcode.com/sota/question-generation-on-squad11).
 
 
 ### Supported Tasks and Leaderboards
-* `question-generation`: The dataset can be used to train a model for question generation.
-  Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L score.
+* `question-generation`: The dataset is assumed to be used to train a model for question generation.
+  Success on this task is typically measured by achieving a high BLEU4/METEOR/ROUGE-L/BERTScore/MoverScore (see our paper for more in detail).
   This task has an active leaderboard which can be found at [here](https://paperswithcode.com/sota/question-generation-on-squad11).
 
 ### Languages