Add First Author column with links

app.py

@@ -49,7 +49,7 @@ def build_tab(df, name):
     datasets = sorted(df["Dataset"].unique().tolist())
     models = sorted(df["Model"].unique().tolist())
     organizations = sorted(df["Organization"].unique().tolist())
-    metric_cols = [col for col in df.columns if col not in ["Model", "Organization", "Dataset"]]
+    metric_cols = [col for col in df.columns if col not in ["Model", "Organization", "Dataset", "First Author", "Author Link"]]
 
     # Create pivoted dataframe
     pivoted_data = []
@@ -57,7 +57,14 @@ def build_tab(df, name):
         for org in organizations:
             model_org_data = df[(df["Model"] == model) & (df["Organization"] == org)]
             if not model_org_data.empty:
-                row = {"Model": model, "Organization": org}
+                # Get First Author and Author Link from the first entry (they should be the same for model+org)
+                first_author = model_org_data["First Author"].values[0]
+                author_link = model_org_data["Author Link"].values[0]
+
+                # Create HTML link for First Author
+                author_html = f'<a href="{author_link}" target="_blank">{first_author}</a>'
+
+                row = {"Model": model, "Organization": org, "First Author": author_html}
                 for dataset in datasets:
                     dataset_data = model_org_data[model_org_data["Dataset"] == dataset]
                     if not dataset_data.empty:
@@ -78,7 +85,7 @@ def build_tab(df, name):
         for metric in metric_cols:
             metric_combo_cols.append(f"{dataset} ({metric})")
 
-    all_cols = ["Model", "Organization"] + metric_combo_cols
+    all_cols = ["Model", "Organization", "First Author"] + metric_combo_cols
 
     with gr.TabItem(name, elem_id="llm-benchmark-tab-table"):
         with gr.Row():
@@ -100,7 +107,8 @@ def build_tab(df, name):
                     value=pivoted_df,
                     wrap=True,
                     interactive=False,
-                    elem_id="leaderboard-table"
+                    elem_id="leaderboard-table",
+                    datatype=["str"] * len(pivoted_df.columns)
                 )
 
             with gr.Column(scale=1):
@@ -189,6 +197,22 @@ custom_css = """
     min-width: 100px;
 }
 
+#leaderboard-table tbody td:nth-child(3),
+#leaderboard-table thead th:nth-child(3) {
+    text-align: left;
+    min-width: 120px;
+}
+
+/* Style links in First Author column */
+#leaderboard-table a {
+    color: #0066cc;
+    text-decoration: none;
+}
+
+#leaderboard-table a:hover {
+    text-decoration: underline;
+}
+
 /* Remove any interactive elements from table */
 #leaderboard-table input[type="range"],
 #leaderboard-table .slider {

data/classification.csv

@@ -1,16 +1,16 @@
-Model,Organization,Dataset,Accuracy,F1-Score
-ResNet-50,Microsoft,DoMars16,92.5,91.8
-ViT-Base,Google,DoMars16,94.2,93.5
-Swin-T,Microsoft,DoMars16,95.8,94.9
-InceptionV3,Google,DoMars16,93.1,92.4
-SqueezeNet,DeepMind,DoMars16,89.7,88.6
-ResNet-50,Microsoft,Atmospheric Dust,88.3,87.5
-ViT-Base,Google,Atmospheric Dust,90.1,89.2
-Swin-T,Microsoft,Atmospheric Dust,91.5,90.7
-InceptionV3,Google,Atmospheric Dust,89.8,88.9
-SqueezeNet,DeepMind,Atmospheric Dust,87.2,86.3
-ResNet-50,Microsoft,Martian Frost,85.6,84.8
-ViT-Base,Google,Martian Frost,87.9,86.9
-Swin-T,Microsoft,Martian Frost,88.4,87.5
-InceptionV3,Google,Martian Frost,86.7,85.8
-SqueezeNet,DeepMind,Martian Frost,84.3,83.4
+Model,Organization,Dataset,Accuracy,F1-Score,First Author,Author Link
+ResNet-50,Microsoft,DoMars16,92.5,91.8,K. He,https://kaiminghe.github.io/
+ViT-Base,Google,DoMars16,94.2,93.5,A. Dosovitskiy,https://scholar.google.com/citations?user=UfvnhKcAAAAJ
+Swin-T,Microsoft,DoMars16,95.8,94.9,Z. Liu,https://scholar.google.com/citations?user=nHh9PSsAAAAJ
+InceptionV3,Google,DoMars16,93.1,92.4,C. Szegedy,https://scholar.google.com/citations?user=3QeF7mAAAAAJ
+SqueezeNet,DeepMind,DoMars16,89.7,88.6,F. Iandola,https://scholar.google.com/citations?user=LvWAIwUAAAAJ
+ResNet-50,Microsoft,Atmospheric Dust,88.3,87.5,K. He,https://kaiminghe.github.io/
+ViT-Base,Google,Atmospheric Dust,90.1,89.2,A. Dosovitskiy,https://scholar.google.com/citations?user=UfvnhKcAAAAJ
+Swin-T,Microsoft,Atmospheric Dust,91.5,90.7,Z. Liu,https://scholar.google.com/citations?user=nHh9PSsAAAAJ
+InceptionV3,Google,Atmospheric Dust,89.8,88.9,C. Szegedy,https://scholar.google.com/citations?user=3QeF7mAAAAAJ
+SqueezeNet,DeepMind,Atmospheric Dust,87.2,86.3,F. Iandola,https://scholar.google.com/citations?user=LvWAIwUAAAAJ
+ResNet-50,Microsoft,Martian Frost,85.6,84.8,K. He,https://kaiminghe.github.io/
+ViT-Base,Google,Martian Frost,87.9,86.9,A. Dosovitskiy,https://scholar.google.com/citations?user=UfvnhKcAAAAJ
+Swin-T,Microsoft,Martian Frost,88.4,87.5,Z. Liu,https://scholar.google.com/citations?user=nHh9PSsAAAAJ
+InceptionV3,Google,Martian Frost,86.7,85.8,C. Szegedy,https://scholar.google.com/citations?user=3QeF7mAAAAAJ
+SqueezeNet,DeepMind,Martian Frost,84.3,83.4,F. Iandola,https://scholar.google.com/citations?user=LvWAIwUAAAAJ

data/detection.csv

@@ -1,16 +1,16 @@
-Model,Organization,Dataset,mAP,IoU
-Faster R-CNN,Meta,Mars Crater,78.5,0.72
-YOLOv5,Ultralytics,Mars Crater,80.2,0.74
-DETR,Meta,Mars Crater,82.1,0.76
-RetinaNet,Meta,Mars Crater,79.3,0.73
-SSD,Google,Mars Crater,77.8,0.71
-Faster R-CNN,Meta,Rover Component,75.6,0.69
-YOLOv5,Ultralytics,Rover Component,77.3,0.71
-DETR,Meta,Rover Component,78.9,0.73
-RetinaNet,Meta,Rover Component,76.7,0.70
-SSD,Google,Rover Component,75.1,0.68
-Faster R-CNN,Meta,Geological Feature,73.4,0.67
-YOLOv5,Ultralytics,Geological Feature,75.1,0.69
-DETR,Meta,Geological Feature,76.7,0.71
-RetinaNet,Meta,Geological Feature,74.5,0.68
-SSD,Google,Geological Feature,73.0,0.67
+Model,Organization,Dataset,mAP,IoU,First Author,Author Link
+Faster R-CNN,Meta,Mars Crater,78.5,0.72,S. Ren,https://scholar.google.com/citations?user=L_hq4a0AAAAJ
+YOLOv5,Ultralytics,Mars Crater,80.2,0.74,G. Jocher,https://github.com/glenn-jocher
+DETR,Meta,Mars Crater,82.1,0.76,N. Carion,https://scholar.google.com/citations?user=p1wMCUUAAAAJ
+RetinaNet,Meta,Mars Crater,79.3,0.73,T. Lin,https://scholar.google.com/citations?user=7zQoaFkAAAAJ
+SSD,Google,Mars Crater,77.8,0.71,W. Liu,https://scholar.google.com/citations?user=PQ7QBjYAAAAJ
+Faster R-CNN,Meta,Rover Component,75.6,0.69,S. Ren,https://scholar.google.com/citations?user=L_hq4a0AAAAJ
+YOLOv5,Ultralytics,Rover Component,77.3,0.71,G. Jocher,https://github.com/glenn-jocher
+DETR,Meta,Rover Component,78.9,0.73,N. Carion,https://scholar.google.com/citations?user=p1wMCUUAAAAJ
+RetinaNet,Meta,Rover Component,76.7,0.70,T. Lin,https://scholar.google.com/citations?user=7zQoaFkAAAAJ
+SSD,Google,Rover Component,75.1,0.68,W. Liu,https://scholar.google.com/citations?user=PQ7QBjYAAAAJ
+Faster R-CNN,Meta,Geological Feature,73.4,0.67,S. Ren,https://scholar.google.com/citations?user=L_hq4a0AAAAJ
+YOLOv5,Ultralytics,Geological Feature,75.1,0.69,G. Jocher,https://github.com/glenn-jocher
+DETR,Meta,Geological Feature,76.7,0.71,N. Carion,https://scholar.google.com/citations?user=p1wMCUUAAAAJ
+RetinaNet,Meta,Geological Feature,74.5,0.68,T. Lin,https://scholar.google.com/citations?user=7zQoaFkAAAAJ
+SSD,Google,Geological Feature,73.0,0.67,W. Liu,https://scholar.google.com/citations?user=PQ7QBjYAAAAJ

data/segmentation.csv

@@ -1,16 +1,16 @@
-Model,Organization,Dataset,Dice Score,IoU
-U-Net,OpenAI,Mars Terrain,0.85,0.74
-DeepLabV3+,Google,Mars Terrain,0.87,0.76
-Mask R-CNN,Meta,Mars Terrain,0.88,0.78
-SegFormer,NVIDIA,Mars Terrain,0.86,0.75
-HRNet,Microsoft,Mars Terrain,0.84,0.73
-U-Net,OpenAI,Dust Storm,0.82,0.70
-DeepLabV3+,Google,Dust Storm,0.84,0.72
-Mask R-CNN,Meta,Dust Storm,0.85,0.74
-SegFormer,NVIDIA,Dust Storm,0.83,0.71
-HRNet,Microsoft,Dust Storm,0.82,0.70
-U-Net,OpenAI,Geological Feature,0.81,0.68
-DeepLabV3+,Google,Geological Feature,0.83,0.70
-Mask R-CNN,Meta,Geological Feature,0.84,0.72
-SegFormer,NVIDIA,Geological Feature,0.82,0.69
-HRNet,Microsoft,Geological Feature,0.81,0.68
+Model,Organization,Dataset,Dice Score,IoU,First Author,Author Link
+U-Net,OpenAI,Mars Terrain,0.85,0.74,O. Ronneberger,https://scholar.google.com/citations?user=MXXkjXkAAAAJ
+DeepLabV3+,Google,Mars Terrain,0.87,0.76,L. Chen,https://scholar.google.com/citations?user=WicCTRsAAAAJ
+Mask R-CNN,Meta,Mars Terrain,0.88,0.78,K. He,https://kaiminghe.github.io/
+SegFormer,NVIDIA,Mars Terrain,0.86,0.75,E. Xie,https://scholar.google.com/citations?user=txgkZ0kAAAAJ
+HRNet,Microsoft,Mars Terrain,0.84,0.73,J. Wang,https://scholar.google.com/citations?user=aYKQn88AAAAJ
+U-Net,OpenAI,Dust Storm,0.82,0.70,O. Ronneberger,https://scholar.google.com/citations?user=MXXkjXkAAAAJ
+DeepLabV3+,Google,Dust Storm,0.84,0.72,L. Chen,https://scholar.google.com/citations?user=WicCTRsAAAAJ
+Mask R-CNN,Meta,Dust Storm,0.85,0.74,K. He,https://kaiminghe.github.io/
+SegFormer,NVIDIA,Dust Storm,0.83,0.71,E. Xie,https://scholar.google.com/citations?user=txgkZ0kAAAAJ
+HRNet,Microsoft,Dust Storm,0.82,0.70,J. Wang,https://scholar.google.com/citations?user=aYKQn88AAAAJ
+U-Net,OpenAI,Geological Feature,0.81,0.68,O. Ronneberger,https://scholar.google.com/citations?user=MXXkjXkAAAAJ
+DeepLabV3+,Google,Geological Feature,0.83,0.70,L. Chen,https://scholar.google.com/citations?user=WicCTRsAAAAJ
+Mask R-CNN,Meta,Geological Feature,0.84,0.72,K. He,https://kaiminghe.github.io/
+SegFormer,NVIDIA,Geological Feature,0.82,0.69,E. Xie,https://scholar.google.com/citations?user=txgkZ0kAAAAJ
+HRNet,Microsoft,Geological Feature,0.81,0.68,J. Wang,https://scholar.google.com/citations?user=aYKQn88AAAAJ