Datasets:

dyfang
/

trace2action-10k-ground-cot

dataset_info:
  features:
    - name: task_id
      dtype: int64
    - name: platform
      dtype: string
    - name: instruction
      dtype: string
    - name: step_index
      dtype: int32
    - name: image
      dtype: image
    - name: code
      dtype: string
    - name: action
      dtype: string
    - name: groundcua
      dtype: string
    - name: action_history
      dtype: string
    - name: observation
      dtype: string
    - name: thought
      dtype: string
    - name: action_description
      dtype: string
    - name: reflection
      dtype: string
  splits:
    - name: train
      num_bytes: 2270463289
      num_examples: 8599
    - name: test
      num_bytes: 590129663
      num_examples: 2355
  download_size: 2682099164
  dataset_size: 2860592952
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

Trace2Action 10K Dataset

Trace2Action is a large-scale computer-use dataset for finetuning and evaluating multimodal agents that operate GUIs directly with actions. It is collected using real desktop interaction recordings with synchronized screen video, click activity, and keyboard events. This creates an opportunity to study computer-use agents with direct action supervision from real human behavior.

Structure

Field	Type	Description
`task_id`	string	Unique trajectory identifier
`platform`	string	Application platform name
`instruction`	string	Natural language task objective
`step_index`	int32	Temporal index within trajectory
`image`	Image	Screenshot corresponding to current state
`code`	string	Ground-truth executable UI action
`action`	string	Action description in JSON format
`groundcua`	json	List of bounding boxes in JSON format
`action_history`	json	Action history in JSON format
`observation`	string	Structured state interpretation
`thought`	string	Intermediate reasoning process
`action_description`	string	Natural language action description
`reflection`	string	Retrospective procedural reflection

Action space

{"type": "CLICK", "x": [0, 100], "y": [0, 100] }
{"type": "RIGHT_CLICK", "x": [0, 100], "y": [0, 100]}
{"type": "DOUBLE_CLICK", "x": [0, 100], "y": [0, 100]}
{"type": "DRAG_TO", "x": [0, 100], "y": [0, 100]}
{"type": "SCROLL", "amount": <int>}
{"type": "PRESS", "key": "<str>"}
{"type": "HOTKEY", "keys": ["<str>", "<str>"]}
{"type": "TYPE", "text": "<str>"}

Applications

Train set (20):

7-Zip
Affine
Atom
Anki
Bash
Blender
Chromium
Element
Eclipse
FreeCAD
GIMP
Inkscape
IntelliJ IDEA
LibreOffice Calc
LibreOffice Draw
LibreOffice Writer
Mastodon
Nextcloud
OnlyOffice Calendar
OnlyOffice Presentation

Test set (4):

Gedit
LibreOffice Impress
Matrix
OBS Studio

Download

from datasets import load_dataset
ds = load_dataset("dyfang/trace2action-10k-ground-cot")