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vgbench/VGQA

The VGQA dataset is the first comprehensive benchmark for evaluating large language models (LLMs) on vector graphics processing and generation capabilities.

Updated 7/16/2024
hugging_face

Description

VGQA Dataset

Overview

  • Task Category: Visual Question Answering (visual-question-answering)
  • Dataset Scale: 1K < n < 10K

Citation

  • BibTeX:

    @misc{zou2024vgbenchevaluatinglargelanguage, title={VGBench: Evaluating Large Language Models on Vector Graphics Understanding and Generation}, author={Bocheng Zou and Mu Cai and Jianrui Zhang and Yong Jae Lee}, year={2024}, eprint={2407.10972}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2407.10972}, }

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Topics

Visual Question Answering
Vector Graphics Understanding

Source

Organization: hugging_face

Created: Unknown

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