Update src/about.py

src/about.py

@@ -27,7 +27,7 @@ TITLE = """<h1 align="center" id="space-title">Open Persian LLM Alignment Leader
 
 # What does your leaderboard evaluate?
 INTRODUCTION_TEXT = """
-Intro text
+Open Persian LLM Alignment Leaderboard
 """
 
 # Which evaluations are you running? how can people reproduce what you have?
@@ -39,19 +39,20 @@ Addressing the gaps in existing LLM evaluation frameworks, this benchmark is spe
     1. Translated datasets (adapted from established English benchmarks)
     2. Synthetically generated data (newly created for Persian LLMs)
     3. Naturally collected data (reflecting indigenous cultural nuances)
-Key Datasets in the Benchmark
+    
+### Key Datasets in the Benchmark
 The benchmark integrates the following datasets to ensure a robust evaluation of Persian LLMs:
 Translated Datasets
     • Anthropic-fa
     • AdvBench-fa
     • HarmBench-fa
     • DecodingTrust-fa
-Newly Developed Persian Datasets
+### Newly Developed Persian Datasets
     • ProhibiBench-fa: Evaluates harmful and prohibited content in Persian culture.
     • SafeBench-fa: Assesses safety in generated outputs.
     • FairBench-fa: Measures bias mitigation in Persian LLMs.
     • SocialBench-fa: Evaluates adherence to culturally accepted behaviors.
-Naturally Collected Persian Dataset
+### Naturally Collected Persian Dataset
     • GuardBench-fa: A large-scale dataset designed to align Persian LLMs with local cultural norms.
 A Unified Framework for Persian LLM Evaluation
 By combining these datasets, our work establishes a culturally grounded alignment evaluation framework, enabling systematic assessment across three key aspects: