Update README.md

README.md

@@ -4,7 +4,7 @@ license: apache-2.0
 
 Here we create two datasets (from existing datasets: CLEVRER, VisualGenome) for the Object Counting instruction tuning task.
 
-### CLEVRER
+### CLEVRER, a video dataset
 
 CLEVRER has QA pairs for each 5000 training videos.
 ```json
@@ -12,14 +12,14 @@ CLEVRER has QA pairs for each 5000 training videos.
 ```
 We select 'descriptive' type, 'count' subtype questions, they are object counting task questions. In the 'program' list, it shows how complex the question is (longer means more complex), so we filter out those longer than 9 to reduce difficulty.
 
-CLEVRER contains both positive questions and negative (non-exist) questions, so no need to construct negative samples.
+CLEVRER contains both positive questions and negative (asking for non-exist objects) questions, so we skip generating negative samples for CLEVRER.
 
 Some questions are 'event' specific, counting moving/stationary objects when a certain event happens. i.e., 'How many objects are stationary when the yellow object enters the scene?'
 
 Downloading videos from: http://clevrer.csail.mit.edu/
 
 
-### VisualGenome
+### VisualGenome, a image dataset
 
 We generate some negative questions for non-exist objects in the image. We use the version 1 image sets. Download from: https://homes.cs.washington.edu/~ranjay/visualgenome/api.html