Update README.md

README.md

@@ -60,6 +60,16 @@ Multimodal-Mind2Web is the multimodal version of [Mind2Web](https://osu-nlp-grou
 
 ## Dataset Structure
 
+### Data Splits
+- train: 1009 tasks.
+- test: 
+    - Cross Task: 1339 actions from 177 tasks. Tasks from the same website are seen during training. 
+    - Cross Website: 1019 actions from 142 tasks. Websites are not seen during training.
+    - Cross Domain: 4060 actions from 694 tasks. Entire domains are not seen during training.
+
+The three test set splits have went through human verification to confirm element visibility and correct rendering for action prediction. 
+
+Each line in the dataset is an action consisting of screenshot image, HTML text and other fields required for action prediction, for the convenience of inference. 
 
 ### Data Fields
 
@@ -69,30 +79,22 @@ Multimodal-Mind2Web is the multimodal version of [Mind2Web](https://osu-nlp-grou
 - "subdomain" (str): website subdomain
 - "confirmed_task" (str): task description
 - "action_reprs" (list[str]): human readable string representation of the action sequence
-- "actions" (list[dict]): list of actions (steps) to complete the task
--   - "screenshot" (str): path to the webpage screenshot image corresponding to the HTML.
-    - "action_uid" (str): unique id for each action (step)
-    - "raw_html" (str): raw html of the page before the action is performed
-    - "cleaned_html" (str): cleaned html of the page before the action is performed
-    - "operation" (dict): operation to perform
-        - "op" (str): operation type, one of CLICK, TYPE, SELECT
-        - "original_op" (str): original operation type, contain additional HOVER and ENTER that are mapped to CLICK, not used
-        - "value" (str): optional value for the operation, e.g., text to type, option to select
-    - "pos_candidates" (list[dict]): ground truth elements. Here we only include positive elements that exist in "cleaned_html" after our preprocessing, so "pos_candidates" might be empty. The original labeled element can always be found in the "raw_html".
-        - "tag" (str): tag of the element
-        - "is_original_target" (bool): whether the element is the original target labeled by the annotator
-        - "is_top_level_target" (bool): whether the element is a top level target find by our algorithm. please see the paper for more details.
-        - "backend_node_id" (str): unique id for the element
-        - "attributes" (str): serialized attributes of the element, use `json.loads` to convert back to dict
-    - "neg_candidates" (list[dict]): other candidate elements in the page after preprocessing, has similar structure as "pos_candidates"
+- "screenshot" (str): path to the webpage screenshot image corresponding to the HTML.
+- "action_uid" (str): unique id for each action (step)
+- "raw_html" (str): raw html of the page before the action is performed
+- "cleaned_html" (str): cleaned html of the page before the action is performed
+- "operation" (dict): operation to perform
+  - "op" (str): operation type, one of CLICK, TYPE, SELECT
+  - "original_op" (str): original operation type, contain additional HOVER and ENTER that are mapped to CLICK, not used
+  - "value" (str): optional value for the operation, e.g., text to type, option to select
+- "pos_candidates" (list[dict]): ground truth elements. Here we only include positive elements that exist in "cleaned_html" after our preprocessing, so "pos_candidates" might be empty. The original labeled element can always be found in the "raw_html".
+  - "tag" (str): tag of the element
+  - "is_original_target" (bool): whether the element is the original target labeled by the annotator
+  - "is_top_level_target" (bool): whether the element is a top level target find by our algorithm. please see the paper for more details.
+  - "backend_node_id" (str): unique id for the element
+  - "attributes" (str): serialized attributes of the element, use `json.loads` to convert back to dict
+- "neg_candidates" (list[dict]): other candidate elements in the page after preprocessing, has similar structure as "pos_candidates"
 
-### Data Splits
-
-- train: 1,009 instances
-- test: 
-    - Cross Task: 177 instances, tasks from the same website are seen during training
-    - Cross Website: 142 instances, websites are not seen during training
-    - Cross Domain: 694 instances, entire domains are not seen during training
 
 
 ### Disclaimer