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Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs

Dysca is a dynamic and scalable benchmark for evaluating the perception ability of Large Vision-Language Models (LVLMs) via various subtasks and scenarios.

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Cite this as

Jie Zhang, Zhongqi Wang, Mengqi Lei, Zheng Yuan, Bei Yan, Shiguang Shan, Xilin Chen (2024). Dataset: Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs. https://doi.org/10.57702/ggkr5ugt

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2406.18849
Author	Jie Zhang
More Authors	Zhongqi Wang Mengqi Lei Zheng Yuan Bei Yan Shiguang Shan Xilin Chen
Homepage	https://github.com/Benchmark-Dysca/Dysca