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VISION_LANGUAGE / README.md
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metadata
license: cdla-permissive-2.0
dataset_info:
  - config_name: maze
    features:
      - name: id
        dtype: int32
      - name: image
        dtype: image
      - name: prompt
        dtype: string
      - name: ground_truth
        dtype: string
      - name: task
        dtype: string
      - name: question_type
        dtype: string
      - name: target_options
        dtype: string
  - config_name: maze_text_only
    features:
      - name: id
        dtype: int32
      - name: prompt
        dtype: string
      - name: ground_truth
        dtype: string
      - name: task
        dtype: string
      - name: question_type
        dtype: string
      - name: target_options
        dtype: string
  - config_name: spatial_grid
    features:
      - name: id
        dtype: int32
      - name: image
        dtype: image
      - name: prompt
        dtype: string
      - name: ground_truth
        dtype: string
      - name: task
        dtype: string
      - name: question_type
        dtype: string
      - name: target_options
        dtype: string
  - config_name: spatial_grid_text_only
    features:
      - name: id
        dtype: int32
      - name: prompt
        dtype: string
      - name: ground_truth
        dtype: string
      - name: task
        dtype: string
      - name: question_type
        dtype: string
      - name: target_options
        dtype: string
  - config_name: spatial_map
    features:
      - name: id
        dtype: int32
      - name: image
        dtype: image
      - name: prompt
        dtype: string
      - name: ground_truth
        dtype: string
      - name: task
        dtype: string
      - name: question_type
        dtype: string
      - name: target_options
        dtype: string
  - config_name: spatial_map_text_only
    features:
      - name: id
        dtype: int32
      - name: prompt
        dtype: string
      - name: ground_truth
        dtype: string
      - name: task
        dtype: string
      - name: question_type
        dtype: string
      - name: target_options
        dtype: string
configs:
  - config_name: maze
    data_files:
      - split: val
        path: maze/maze_val.parquet
  - config_name: maze_text_only
    data_files:
      - split: val
        path: maze/maze_text_only_val.parquet
  - config_name: spatial_grid
    data_files:
      - split: val
        path: spatial_grid/spatial_grid_val.parquet
  - config_name: spatial_grid_text_only
    data_files:
      - split: val
        path: spatial_grid/spatial_grid_text_only_val.parquet
  - config_name: spatial_map
    data_files:
      - split: val
        path: spatial_map/spatial_map_val.parquet
  - config_name: spatial_map_text_only
    data_files:
      - split: val
        path: spatial_map/spatial_map_text_only_val.parquet

A key question for understanding multimodal vs. language capabilities of models is what is the relative strength of the spatial reasoning and understanding in each modality, as spatial understanding is expected to be a strength for multimodality? To test this we created a procedurally generatable, synthetic dataset to testing spatial reasoning, navigation, and counting. These datasets are challenging and by being procedurally generated new versions can easily be created to combat the effects of models being trained on this data and the results being due to memorization. For each task, each question has an image and a text representation that is sufficient for answering each question.

This dataset has three tasks that test: Spatial Understanding (Spatial-Map), Nav- igation (Maze), and Counting (Spatial-Grid). Each task has three conditions, with respect to the input modality, 1) text-only, input and a question, 2) vision-only, which is the standard task of visual-question an- swering that consists of a vision-only input and a question, and 3) vision-text includes both text and image representations with the question. Each condition includes 1500 images and text pairs for a total of 4500.

Spatial Map

The dataset consists of spatial relationships for random layouts of symbolic objects with text names on white background. Each object is associated with a unique location name, such as Unicorn Umbrellas and Gale Gifts. To study the impact of modality, the textual representation of each input consists of pairwise relations such as Brews Brothers Pub is to the Southeast of Whale’s Watches. The questions include asking about the spatial relationships between two locations and the number of objects that meet specific spatial criteria.

The dataset includes 3 conditions: text only, image only, and text+image. Each condition includes 1500 images and text pairs for a total of 4500.

There are 3 question types: 1) In which direction is one object to another (answer is a direction) 2) Which object is to the direction of another (answer is an object name) 3) How many objects are in a direction of another (answer is a number)

Each question is multiple choice.

Maze

The dataset consists of small mazes with questions asked about the maze. Each sample can be represented as colored blocks where different colors signify distinct elements: a green block marks the starting point (S), a red block indicates the exit (E), black blocks represent impassable walls, white blocks denote navigable paths, and blue blocks trace the path from S to E. The objective is to navigate from S to E following the blue path, with movement permitted in the four cardinal directions (up, down, left, right). Alternatively, each input can be depicted in textual format using ASCII code. The questions asked include counting the number of turns from S to E and determining the spatial relationship between S and E.

The dataset includes 3 conditions: text only, image only, and text+image. Each condition includes 1500 images and text pairs for a total of 4500.

There are 3 question types: 1) How many right turns on the path from start to end (answer is a number) 2) How many total turns on the path from start to end (answer is a number) 3) Where is the exit releative to the start (answer is direction or yes/no)

Each question is multiple choice.

Spatial Grid

Each input consists of a grid of cells, each containing an image (e.g.,a rabbit). Alternatively, this grid can also be represented in a purely textual format; for instance, the first row might be described as: elephant | cat | giraffe | elephant | cat. The evaluations focus on tasks such as counting specific objects (e.g., rabbits) and identifying the object located at a specific coordinate in the grid (e.g., first row, second column).

The dataset includes 3 conditions: text only, image only, and text+image. Each condition includes 1500 images and text pairs for a total of 4500 questions.

There are 3 question types: 1) How many blocks contain a specific animal (answer is a number) 2) What animal is in one specific block, adressed by top-left, top, right, etc. (answer is an animal name) 3) What animal is in one specific block, addressed by row, column (answer is an animal name)

Each question is multiple choice.


More details here: https://arxiv.org/pdf/2406.14852