Datasets:

ImanAndrea
/

citation_annotations

@@ -14,5 +14,13 @@
     "label": "Coherence",
     "user": "Iraa",
     "text": "First, dense retrieval models need a large amount of labeled training data for a decent performance. However, as Figure 1 shows, the proportion of labeled query-document pairs is extremely small since it is almost impossible to rely on humans for the annotations of a large document corpus. Second, in order to adapt a retrieval model to the real world, where documents constantly emerge, handling unlabeled documents that are not seen during training should obviously be considered, but remains challenging."
   }
 ]

     "label": "Coherence",
     "user": "Iraa",
     "text": "First, dense retrieval models need a large amount of labeled training data for a decent performance. However, as Figure 1 shows, the proportion of labeled query-document pairs is extremely small since it is almost impossible to rely on humans for the annotations of a large document corpus. Second, in order to adapt a retrieval model to the real world, where documents constantly emerge, handling unlabeled documents that are not seen during training should obviously be considered, but remains challenging."
+  },
+  {
+    "file": "paper_98.txt",
+    "start": 3790,
+    "end": 3848,
+    "label": "Unsupported claim",
+    "user": "Iraa",
+    "text": " against various evaluation metrics for retrieval models. "
   }
 ]