update

about.py

@@ -16,7 +16,7 @@ def render_about():
             
             with gr.Accordion("1. PerCoR (Persian Commonsense Reasoning)", open=False):
                 gr.Markdown("""
-                PersCoR is the first large-scale Persian benchmark for evaluating models' ability in **commonsense reasoning** through multi-choice sentence completion. It includes over 106,000 samples from diverse domains such as news, religion, and lifestyle, extracted from more than 40 Persian websites. Innovative methods like "segmentation by conjunctions" were used to create coherent and diverse sentences and options, while the DRESS-AF technique helped generate challenging, human-solvable distractors.
+                PerCoR is the first large-scale Persian benchmark for evaluating models' ability in **commonsense reasoning** through multi-choice sentence completion. It includes over 106,000 samples from diverse domains such as news, religion, and lifestyle, extracted from more than 40 Persian websites. Innovative methods like "segmentation by conjunctions" were used to create coherent and diverse sentences and options, while the DRESS-AF technique helped generate challenging, human-solvable distractors.
                 """)
 
             with gr.Accordion("2. Persian IFEval (Persian Instruction Following Evaluation)", open=False):

app.py

@@ -25,7 +25,7 @@ def create_app():
     logger.info("Initializing MIZAN: A Persian LLM Leaderboard application...")
 
     # Define the path to the leaderboard's configuration file
-    # This assumes app.py is in the project root, and column_config.yaml is inside the 'leaderboard' directory.
+    # This assumes app.py is in the project root, and leaderboard_config.yaml is inside the 'leaderboard' directory.
     config_file_path = Path("leaderboard/leaderboard_config.yaml")
 
     if not config_file_path.exists():

leaderboard/leaderboard_config.yaml

@@ -43,8 +43,8 @@ task_display_names:
   translation-fa2en_fa2en: "Translation (fa2en)"
   translation-ar2fa_ar2fa: "Translation (ar2fa)"
   translation-fa2ar_fa2ar: "Translation (fa2ar)"
-  summarization_SamSUM-fa: "SamSum-Fa (Summarizaion)"
-  summarization_PnSummary: "PnSummary (Summarizaion)"
+  summarization_SamSUM-fa: "SamSum-Fa (Summarization)"
+  summarization_PnSummary: "PnSummary (Summarization)"
   sentiment-analysis_deepsentipers: "DeepSentiPers (SA)"
   sts_SynPerSTS: "SynPerSTS (STS)"
   ner_arman: "Arman (NER)"