Update full datasets description in About V1.3 by Akim

src/about.py

@@ -77,11 +77,9 @@ TITLE = """<h1 align="center" id="space-title">Open Japanese LLM Leaderboard by
 INTRODUCTION_TEXT = """
 🇯🇵 The Open Japanese LLM Leaderboard 🌸 by [LLM-Jp](https://llm-jp.nii.ac.jp/en/) evaluates the performance of Japanese Large Language Models (LLMs).
 
-This leaderboard was built by [LLM-Jp](https://llm-jp.nii.ac.jp/en/), a cross-organizational project for the research and development of Japanese large language models (LLMs). Organized by the National Institute of Informatics, LLM-jp aims to develop open-source and strong Japanese LLMs, and as of this writing, more than 1,500 participants from academia and industry are working together for this purpose.
+This leaderboard was built by contributors of [LLM-Jp](https://llm-jp.nii.ac.jp/en/), a cross-organizational project for the research and development of Japanese large language models (LLMs). Organized by the National Institute of Informatics, LLM-jp aims to develop open-source and strong Japanese LLMs with more than 1,500 participants from academia and industry as of July 2024.
 
-When you submit a model on the "Submit here!" page, it is automatically evaluated on a set of benchmarks.This Open Japanese LLM Leaderboard assesses language understanding, of Japanese LLMs with more than 52 benchmarks from classical to modern NLP tasks such as Natural language inference, Question Answering, Machine Translation, Code Generation, Mathematical reasoning, Summarization, etc.
-
-For more information about benchmarks, and datasets, please consult the "About" page. For more details, please refer to the website of [LLM-Jp](https://llm-jp.nii.ac.jp/en/)
+This Open Japanese LLM Leaderboard assesses language understanding, of Japanese LLMs with more than 52 benchmarks from classical to modern NLP tasks such as Natural language inference, Question Answering, Machine Translation, Code Generation, Mathematical reasoning, Summarization, etc. When you submit a model on the "Submit here!" page, it is automatically evaluated on a set of benchmarks. For more information about benchmarks, please consult the "About" page. For more details, please refer to the website of [LLM-Jp](https://llm-jp.nii.ac.jp/en/)
 
 """
 
@@ -129,12 +127,7 @@ LLM_BENCHMARKS_TEXT = f"""
 **FA (Fundamental Analysis)**
 
 * `Wikipedia Annotated Corpus`, [Source](https://github.com/ku-nlp/WikipediaAnnotatedCorpus) (License CC BY-SA 4.0)
-List of tasks:
-- Reading Prediction
-- Named-entity recognition (NER)
-- Dependency Parsing
-- Predicate-argument structure analysis (PAS)
-- Coreference Resolution
+List of tasks: (Reading Prediction, Named-entity recognition (NER), Dependency Parsing, Predicate-argument structure analysis (PAS), Coreference Resolution)
 
 **MR (Mathematical Reasoning)**