(ALL)

app.py

@@ -106,6 +106,7 @@ with gr.Blocks(css="style.css") as demo:
                     cat_options = gr.CheckboxGroup(
                         label="Category",
                         choices=[
+                            '(ALL)',
                             'cs.*',
                             'eess.*',
                             'econ.*',
@@ -127,7 +128,7 @@ with gr.Blocks(css="style.css") as demo:
                             'q-fin.*',
                             'stat.*',
                         ],
-                        value=["cs.*"]
+                        value=["(ALL)"]
                     )
                     hf_options = gr.CheckboxGroup(
                         label="Hugging Face options",

df/PaperCentral.py

@@ -268,7 +268,6 @@ class PaperCentral:
                     f"<a href='{row['project_page']}'>{row['project_page']}</a>"
                 )
 
-
             return row
 
         df = df.copy()
@@ -346,14 +345,19 @@ class PaperCentral:
 
         # Handle category options
         if cat_options:
-            options = [o.replace(".*", "") for o in cat_options]
-            conference_filter = pd.Series(False, index=filtered_df.index)
-            for option in options:
-                conference_filter |= (
-                        filtered_df['primary_category'].notna() &
-                        filtered_df['primary_category'].str.contains(option, case=False)
-                )
-            filtered_df = filtered_df[conference_filter]
+            if "(ALL)" in cat_options:
+                # If "(ALL)" is selected, include all categories without filtering
+                pass  # No action needed, include all categories
+            else:
+                # Proceed with filtering based on selected categories
+                options = [o.replace(".*", "") for o in cat_options]
+                conference_filter = pd.Series(False, index=filtered_df.index)
+                for option in options:
+                    conference_filter |= (
+                            filtered_df['primary_category'].notna() &
+                            filtered_df['primary_category'].str.contains(option, case=False)
+                    )
+                filtered_df = filtered_df[conference_filter]
 
         # Handle date filtering
         if not conference_options: