Q-align: teaching LMMs for visual scoring via discrete text-defined levels

Q-align: teaching LMMs for visual scoring via discrete text-defined levels

The explosion of visual content available online underscores the requirement for an accurate machine assessor to robustly evaluate scores across diverse types of visual contents. While recent studies have demonstrated the exceptional potentials of large multi-modality models (LMMs) on a wide rang...

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Bibliographic Details
Main Authors: Wu, Haoning, Zhang, Zicheng, Zhang, Weixia, Chen, Chaofeng, Liao, Liang, Li, Chunyi, Gao, Yixuan, Wang, Annan, Zhang, Erli, Sun, Wenxiu, Yan, Qiong, Min, Xiongkuo, Zhai, Guangtao, Lin, Weisi
Other Authors: College of Computing and Data Science
Format: Conference Paper
Language:English
Published: 2024
Subjects:
Computer and Information Science
Large multi-modality models
Computer vision
Online Access:https://hdl.handle.net/10356/178466
http://arxiv.org/abs/2312.17090v1
https://openreview.net/forum?id=PHjkVjR78A
https://icml.cc/

Internet

https://hdl.handle.net/10356/178466
http://arxiv.org/abs/2312.17090v1
https://openreview.net/forum?id=PHjkVjR78A
https://icml.cc/

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