An Early Evaluation of GPT-4V(ision)

Yang Wu, Shilong Wang, Hao Yang, Tian Zheng, Hongbo Zhang +2 more
10/25/2023
cs.CLcs.CV

No official code found. Best implementation: albertwy/GPT-4V-Evaluation (11 stars, last commit 2023-10-26).

Abstract

In this paper, we evaluate different abilities of GPT-4V including visual understanding, language understanding, visual puzzle solving, and understanding of other modalities such as depth, thermal, video, and audio. To estimate GPT-4V's performance, we manually construct 656 test instances and carefully evaluate the results of GPT-4V. The highlights of our findings are as follows: (1) GPT-4V exhibits impressive performance on English visual-centric benchmarks but fails to recognize simple Chinese texts in the images; (2) GPT-4V shows inconsistent refusal behavior when answering questions related to sensitive traits such as gender, race, and age; (3) GPT-4V obtains worse results than GPT-4 (API) on language understanding tasks including general language understanding benchmarks and visual commonsense knowledge evaluation benchmarks; (4) Few-shot prompting can improve GPT-4V's performance on both visual understanding and language understanding; (5) GPT-4V struggles to find the nuances between two similar images and solve the easy math picture puzzles; (6) GPT-4V shows non-trivial performance on the tasks of similar modalities to image, such as video and thermal. Our experimental results reveal the ability and limitations of GPT-4V and we hope our paper can provide some insights into the application and research of GPT-4V.

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Code Implementations(1)

Data for evaluating GPT-4V

110Oct 25, 20232 years ago

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Cite this paper

@article{wu2023early,
  title  = {An Early Evaluation of GPT-4V(ision)},
  author = {Yang Wu and Shilong Wang and Hao Yang and Tian Zheng and Hongbo Zhang and Yanyan Zhao and Bing Qin},
  year   = {2023},
  eprint = {2310.16534},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.16534v1}
}

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