dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: options
list: string
- name: answer
dtype: string
- name: task_plan
dtype: string
- name: image
dtype: image
splits:
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num_examples: 654
- name: 3d_what
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- name: 3d_where
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- name: 3d_what_attribute
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- name: 3d_where_attribute
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- name: 3d_what_distance
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- name: 3d_where_distance
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- name: 3d_what_attribute_distance
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- name: 3d_what_size
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- name: 3d_where_size
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- name: 3d_what_attribute_size
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- name: 2d_how_many
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- name: 2d_what
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- name: 2d_where
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- name: 2d_what_attribute
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- name: 2d_where_attribute
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- name: sg_what_object
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- name: sg_what_attribute
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num_examples: 645
- name: sg_what_relation
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num_examples: 618
download_size: 10589322704
dataset_size: 10645850450
configs:
- config_name: default
data_files:
- split: 3d_how_many
path: data/3d_how_many-*
- split: 3d_what
path: data/3d_what-*
- split: 3d_where
path: data/3d_where-*
- split: 3d_what_attribute
path: data/3d_what_attribute-*
- split: 3d_where_attribute
path: data/3d_where_attribute-*
- split: 3d_what_distance
path: data/3d_what_distance-*
- split: 3d_where_distance
path: data/3d_where_distance-*
- split: 3d_what_attribute_distance
path: data/3d_what_attribute_distance-*
- split: 3d_what_size
path: data/3d_what_size-*
- split: 3d_where_size
path: data/3d_where_size-*
- split: 3d_what_attribute_size
path: data/3d_what_attribute_size-*
- split: 2d_how_many
path: data/2d_how_many-*
- split: 2d_what
path: data/2d_what-*
- split: 2d_where
path: data/2d_where-*
- split: 2d_what_attribute
path: data/2d_what_attribute-*
- split: 2d_where_attribute
path: data/2d_where_attribute-*
- split: sg_what_object
path: data/sg_what_object-*
- split: sg_what_attribute
path: data/sg_what_attribute-*
- split: sg_what_relation
path: data/sg_what_relation-*
Dataset Card for TaskMeAnything-v1-imageqa-2024
TaskMeAnything-v1-imageqa-2024 benchmark dataset
🌐 Website | 📑 Paper | 🤗 Huggingface | 💻 Interface
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TaskMeAnything-v1-2024
TaskMeAnything-v1-imageqa-2024 is a benchmark for reflecting the current progress of MLMs by automatically finding tasks that SOTA MLMs struggle with using the TaskMeAnything Top-K queries.
This benchmark includes 3,279 2d questions, 7,095 3d questions, and 1,896 real image questions that the TaskMeAnything algorithm automatically approximated as challenging for over 12 popular MLMs.
The dataset contains 19 splits, while each splits contains 600+ questions from a specific task generator in TaskMeAnything-v1. For each row of dataset, it includes: image, question, options, answer and its corresponding task plan.
Load TaskMeAnything-v1-2024 ImageQA Dataset
import datasets
dataset_name = 'weikaih/TaskMeAnything-v1-imageqa-2024'
dataset = datasets.load_dataset(dataset_name, split = TASK_GENERATOR_SPLIT)
where TASK_GENERATOR_SPLIT is one of the task generators, eg, 2024_2d_how_many.
Evaluation Results
Overall
Breakdown performance on each task types
Out-of-Scope Use
This dataset should not be used for training models.
Disclaimers
TaskMeAnything and its associated resources are provided for research and educational purposes only. The authors and contributors make no warranties regarding the accuracy or reliability of the data and software. Users are responsible for ensuring their use complies with applicable laws and regulations. The project is not liable for any damages or losses resulting from the use of these resources.
Contact
- Jieyu Zhang: jieyuz2@cs.washington.edu
Citation
BibTeX:
@article{zhang2024task,
title={Task Me Anything},
author={Zhang, Jieyu and Huang, Weikai and Ma, Zixian and Michel, Oscar and He, Dong and Gupta, Tanmay and Ma, Wei-Chiu and Farhadi, Ali and Kembhavi, Aniruddha and Krishna, Ranjay},
journal={arXiv preprint arXiv:2406.11775},
year={2024}
}