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--- |
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license: cdla-permissive-2.0 |
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dataset_info: |
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- config_name: maze |
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features: |
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- name: id |
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dtype: int32 |
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- name: image |
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dtype: image |
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- name: prompt |
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dtype: string |
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- name: ground_truth |
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dtype: string |
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- name: task |
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dtype: string |
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- name: question_type |
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dtype: string |
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- name: target_options |
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dtype: string |
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- config_name: maze_text_only |
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features: |
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- name: id |
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dtype: int32 |
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- name: prompt |
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dtype: string |
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- name: ground_truth |
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dtype: string |
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- name: task |
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dtype: string |
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- name: question_type |
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dtype: string |
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- name: target_options |
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dtype: string |
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- config_name: spatial_grid |
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features: |
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- name: id |
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dtype: int32 |
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- name: image |
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dtype: image |
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- name: prompt |
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dtype: string |
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- name: ground_truth |
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dtype: string |
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- name: task |
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dtype: string |
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- name: question_type |
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dtype: string |
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- name: target_options |
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dtype: string |
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- config_name: spatial_grid_text_only |
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features: |
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- name: id |
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dtype: int32 |
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- name: prompt |
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dtype: string |
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- name: ground_truth |
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dtype: string |
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- name: task |
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dtype: string |
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- name: question_type |
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dtype: string |
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- name: target_options |
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dtype: string |
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- config_name: spatial_map |
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features: |
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- name: id |
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dtype: int32 |
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- name: image |
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dtype: image |
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- name: prompt |
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dtype: string |
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- name: ground_truth |
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dtype: string |
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- name: task |
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dtype: string |
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- name: question_type |
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dtype: string |
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- name: target_options |
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dtype: string |
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- config_name: spatial_map_text_only |
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features: |
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- name: id |
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dtype: int32 |
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- name: prompt |
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dtype: string |
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- name: ground_truth |
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dtype: string |
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- name: task |
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dtype: string |
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- name: question_type |
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dtype: string |
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- name: target_options |
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dtype: string |
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configs: |
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- config_name: maze |
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data_files: |
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- split: val |
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path: maze/maze_val.parquet |
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- config_name: maze_text_only |
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data_files: |
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- split: val |
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path: maze/maze_text_only_val.parquet |
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- config_name: spatial_grid |
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data_files: |
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- split: val |
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path: spatial_grid/spatial_grid_val.parquet |
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- config_name: spatial_grid_text_only |
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data_files: |
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- split: val |
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path: spatial_grid/spatial_grid_text_only_val.parquet |
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- config_name: spatial_map |
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data_files: |
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- split: val |
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path: spatial_map/spatial_map_val.parquet |
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- config_name: spatial_map_text_only |
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data_files: |
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- split: val |
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path: spatial_map/spatial_map_text_only_val.parquet |
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--- |
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A key question for understanding multimodal vs. language capabilities of models is what is |
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the relative strength of the spatial reasoning and understanding in each modality, as spatial understanding is |
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expected to be a strength for multimodality? To test this we created a procedurally generatable, synthetic dataset |
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to testing spatial reasoning, navigation, and counting. These datasets are challenging and by |
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being procedurally generated new versions can easily be created to combat the effects of models being trained |
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on this data and the results being due to memorization. For each task, each question has an image and a text |
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representation that is sufficient for answering each question. |
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This dataset has three tasks that test: Spatial Understanding (Spatial-Map), Nav- |
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igation (Maze), and Counting (Spatial-Grid). Each task has three conditions, with respect to the input |
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modality, 1) text-only, input and a question, 2) vision-only, which is the standard task of visual-question an- |
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swering that consists of a vision-only input and a question, and 3) vision-text includes both text and image |
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representations with the question. Each condition includes 1500 |
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images and text pairs for a total of 4500. |
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__Spatial Map__ |
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The dataset consists of spatial relationships for random layouts of symbolic objects with text names on white background. |
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Each object is associated with a unique location name, such as Unicorn Umbrellas and Gale Gifts. To study the impact of modality, |
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the textual representation of each input consists of pairwise relations such as Brews Brothers Pub |
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is to the Southeast of Whale’s Watches. The questions include asking about the spatial |
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relationships between two locations and the number of objects that meet specific spatial criteria. |
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|
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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. |
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|
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There are 3 question types: |
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1) In which direction is one object to another (answer is a direction) |
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2) Which object is to the direction of another (answer is an object name) |
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3) How many objects are in a direction of another (answer is a number) |
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Each question is multiple choice. |
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__Maze__ |
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The dataset consists of small mazes with questions asked about the maze. Each sample can be |
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represented as colored blocks where different colors signify distinct elements: a green block marks |
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the starting point (S), a red block indicates the exit (E), black blocks represent impassable walls, |
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white blocks denote navigable paths, and blue blocks trace the path from S to E. The objective is to |
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navigate from S to E following the blue path, with movement permitted in the four cardinal directions |
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(up, down, left, right). Alternatively, each input can be depicted in textual format using ASCII code. |
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The questions asked include counting the number of turns from S to E and determining the spatial relationship |
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between S and E. |
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|
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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. |
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|
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There are 3 question types: |
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1) How many right turns on the path from start to end (answer is a number) |
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2) How many total turns on the path from start to end (answer is a number) |
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3) Where is the exit releative to the start (answer is direction or yes/no) |
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Each question is multiple choice. |
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__Spatial Grid__ |
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Each input consists of a grid of cells, each containing an image (e.g.,a rabbit). Alternatively, this grid |
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can also be represented in a purely textual format; for instance, the first row might be described as: |
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elephant | cat | giraffe | elephant | cat. The evaluations focus on tasks such as counting specific objects (e.g., rabbits) and |
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identifying the object located at a specific coordinate in the grid (e.g., first row, second column). |
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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. |
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There are 3 question types: |
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1) How many blocks contain a specific animal (answer is a number) |
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2) What animal is in one specific block, adressed by top-left, top, right, etc. (answer is an animal name) |
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3) What animal is in one specific block, addressed by row, column (answer is an animal name) |
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Each question is multiple choice. |
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--- |
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More details here: https://arxiv.org/pdf/2406.14852 |
