diff --git a/core/data_utils/load_data_lp.py b/core/data_utils/load_data_lp.py
index e3faa2559f..9e86dec3fb 100644
--- a/core/data_utils/load_data_lp.py
+++ b/core/data_utils/load_data_lp.py
@@ -192,6 +192,26 @@ def load_taglp_citationv8(cfg: CN) -> Tuple[Dict[str, Data], List[str]]:
                             )
     return splits, text, data
 
+def load_taplp_pwc_large(cfg: CN) -> Tuple[Dict[str, Data], List[str]]:
+    data = load_graph_pwc_large()
+    text = load_text_pwc_large()
+    
+    if data.is_directed() is True:
+        data.edge_index  = to_undirected(data.edge_index)
+        undirected  = True 
+    else:
+        undirected = data.is_undirected()
+        
+    splits = get_edge_split(data,
+                            undirected,
+                            cfg.device,
+                            cfg.split_index[1],
+                            cfg.split_index[2],
+                            cfg.include_negatives,
+                            cfg.split_labels
+                            )
+    return splits, text, data
+
 
 # TEST CODE
 if __name__ == '__main__':
diff --git a/core/data_utils/load_data_nc.py b/core/data_utils/load_data_nc.py
index 39a1bdd75c..2d80a0d36d 100644
--- a/core/data_utils/load_data_nc.py
+++ b/core/data_utils/load_data_nc.py
@@ -483,7 +483,19 @@ def load_tag_citeseer() -> Tuple[Data, List[str]]:
     text = load_text_citeseer()
     return graph, text
 
+def load_graph_pwc_large():
+    graph = torch.load(FILE_PATH+'core/dataset/pwc_large')
+    return graph 
 
+
+def load_text_pwc_large() -> List[str]:
+    df = pd.read_csv(FILE_PATH + 'core/dataset/pwc_large/pwc_large_papers.csv')
+    return [
+        f'Text: {ti}\n'
+        for ti in zip(df['feat'])
+    ]
+    
+    
 # Test code
 if __name__ == '__main__':
     graph = load_graph_citeseer()
diff --git a/core/model_finetuning/mlp.py b/core/model_finetuning/mlp.py
index 28cfd4e1cc..0e7fcc48eb 100644
--- a/core/model_finetuning/mlp.py
+++ b/core/model_finetuning/mlp.py
@@ -84,7 +84,7 @@ def parse_args() -> argparse.Namespace:
     parser.add_argument('--score', dest='score', type=str, required=False, default='mlp_score',
                         help='decoder name')
 
-    parser.add_argument('--max_iter', dest='max_iter', type=int, required=False, default=1000,
+    parser.add_argument('--max_iter', dest='max_iter', type=int, required=False, default=10,
                         help='decoder name')
 
     parser.add_argument('--repeat', type=int, default=5,
@@ -167,7 +167,7 @@ def project_main():
                 clf.partial_fit(train_dataset, train_labels, classes=classes)
                 print(f'this epoch costs {time.time() - start}')
 
-                if i % 100 == 0:
+                if i % 10 == 0:
                     # Calculate and print metrics for test set
                     test_metrics = get_metrics(clf, test_dataset, test_labels, evaluator_hit, evaluator_mrr)
                     print(test_metrics)