Assessing the Aesthetic Evaluation Capabilities of GPT-4 with Vision: Insights from Group and Individual Assessments

Reber, R., Schwarz, N., and Winkielman, P.: Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver’s Processing Experience?, Personality and Social Psychology Review

2004

Earlier work this paper cites.

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., and Amodei, D.: Language Models are Few-Shot Learners (2020), arXiv:2005.14165

Original

2005

Earlier work this paper cites.

Ke, Y., Tang, X., and Jing, F.: The design of high-level features for photo quality assessment, in 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’06)

2006

Earlier work this paper cites.

Marchesotti, L., Perronnin, F., Larlus, D., and Csurka, G.: Assessing the aesthetic quality of photographs using generic image descriptors, in 2011 International Conference on Computer Vision

2011

Earlier work this paper cites.

Murray, N., Marchesotti, L., and Perronnin, F.: AVA: A large-scale database for aesthetic visual analysis, in 2012 IEEE Conference on Computer Vision and Pattern Recognition

2012

Earlier work this paper cites.

Kao, Y., Wang, C., and Huang, K.: Visual aesthetic quality assessment with a regression model, in 2015 IEEE International Conference on Image Processing (ICIP)

2015

Earlier work this paper cites.

Chatterjee, A. and Vartanian, O.: Neuroscience of aesthetics, Annals of the New York Academy of Sciences

2016

Earlier work this paper cites.

Deng, Y., Loy, C. C., and Tang, X.: Image Aesthetic Assessment: An experimental survey, IEEE Signal Processing Magazine

2017

Cited alongside, same era.

Ren, J., Shen, X., Lin, Z., Mech, R., and Foran, D. J.: Personalized Image Aesthetics, in Proceedings of the IEEE International Conference on Computer Vision (ICCV)

2017

Cited alongside, same era.

Talebi, H. and Milanfar, P.: NIMA: Neural image assessment, IEEE Transactions on Image Processing

2018

Cited alongside, same era.

Li, L., Zhu, H., Zhao, S., Ding, G., and Lin, W.: Personality-Assisted Multi-Task Learning for Generic and Personalized Image Aesthetics Assessment, IEEE Transactions on Image Processing

2020

Cited alongside, same era.

Yang, Y., Xu, L., Li, L., Qie, N., Li, Y., Zhang, P., and Guo, Y.: Personalized Image Aesthetics Assessment With Rich Attributes, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., Chen, Z., Tang, J., Chen, X., Lin, Y., Zhao, W. X., Wei, Z., and Wen, J.-R.: A Survey on Large Language Model based Autonomous Agents (2023), arXiv:2308.11432

Original

2023

Later among the works it cites.

Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., and Zhou, D.: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (2023), arXiv:2201.11903

Original

2023

Later among the works it cites.

Xu, B., Yang, A., Lin, J., Wang, Q., Zhou, C., Zhang, Y., and Mao, Z.: ExpertPrompting: Instructing Large Language Models to be Distinguished Experts (2023), arXiv:2305.14688

Original

2023

Later among the works it cites.

Yang, Z., Li, L., Lin, K., Wang, J., Lin, C.-C., Liu, Z., and Wang, L.: The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) (2023), arXiv:2309.17421

Original

2023

Later among the works it cites.