November Release

static/html_content.py

@@ -112,7 +112,7 @@ REFERENCES_HTML = """
 OTHER_MODELS_HTML = """
 <div style="max-width: 800px; margin: auto; padding: 20px; border: 1px solid #ccc; border-radius: 10px;">
     <p style="font-size: 16px; text-align: start;">
-        This models were previously listed on the main leaderboard and will no longer be updated.
+        These models were previously listed on the main leaderboard, evaluated with a potentially deprecated version of TuRTLe, and will no longer be updated.
     </p>
 </div>
 """

utils.py

@@ -74,6 +74,10 @@ def filter_RTLRepo(subset: pd.DataFrame, name=str) -> pd.DataFrame:
 
     if name == "Other Models":
         filtered_df["Date Discarded"] = filtered_df["Model"].apply(lambda x: DISCARDED_MODELS.get(extract_name_from_link(x), "N/A"))
+
+        # reorder to put Date Discarded between Params and Exact Matching (EM)
+        cols = ["Type", "Model", "Parameters (B)", "Date Discarded", "Exact Matching (EM)"]
+        filtered_df = filtered_df[[c for c in cols if c in filtered_df.columns]]
     return filtered_df
 
 
@@ -126,7 +130,9 @@ def filter_bench(subset: pd.DataFrame, df_agg=None, agg_column=None, name=str) -
 
     if name == "Other Models":
         pivot_df["Date Discarded"] = pivot_df["Model"].apply(lambda x: DISCARDED_MODELS.get(extract_name_from_link(x), "N/A"))
-
+        # reorder to put Date Discarded between Params Syntax
+        cols = ["Type", "Model", "Parameters (B)", "Date Discarded", "Syntax", "Functionality", "Synthesis", "Post-Synthesis"]
+        pivot_df = pivot_df[[c for c in cols if c in pivot_df.columns]]
     return pivot_df
 
 
@@ -192,5 +198,8 @@ def filter_bench_all(subset: pd.DataFrame, df_agg=None, agg_column=None, name=st
 
     if name == "Other Models":
         pivot_df["Date Discarded"] = pivot_df["Model"].apply(lambda x: DISCARDED_MODELS.get(extract_name_from_link(x), "N/A"))
+        # reorder to put Date Discarded between Params Syntax
+        cols = ["Type", "Model", "Parameters (B)", "Date Discarded", "Syntax", "Functionality", "Synthesis", "Post-Synthesis"]
+        pivot_df = pivot_df[[c for c in cols if c in pivot_df.columns]]
 
     return pivot_df