Datasets:
metadata
dataset_info:
features:
- name: id
dtype: string
- name: turncase
dtype: string
- name: num_turns
dtype: int32
- name: prompt_category
dtype: string
- name: eval_focus
dtype: string
- name: prompt
dtype: string
- name: golden_answer
dtype: string
- name: image
dtype: image
- name: images
sequence:
dtype: image
- name: num_images
dtype: int32
- name: tool_trajectory
dtype: string
- name: rubrics
dtype: string
splits:
- name: train
num_bytes: 5981789093
num_examples: 1204
download_size: 5981789093
dataset_size: 5981789093
configs:
- config_name: default
data_files:
- split: train
path: data/*.parquet
VisuAlToolBench is a challenging benchmark to assess tool-enabled visual perception, transformation, and reasoning in multimodal LLMs. It evaluates whether models can not only think about images but also think with images by actively manipulating visuals (e.g., crop, edit, enhance) and integrating general-purpose tools to solve complex tasks. The dataset contains single-turn and multi-turn tasks across diverse domains, each accompanied by detailed rubrics for systematic evaluation. Parquet files under data/ are auto-indexed by the Hub and power the Dataset Viewer.
Paper: BEYOND SEEING: Evaluating Multimodal LLMs on Tool-enabled Image Perception, Transformation, and Reasoning