Singh, A.K., Ding, D., Saxe, A., et al. (2022). Know Your Audience: Specializing Grounded Language Models with the Game of Dixit. arXiv: 2206.08349.
https://doi.org/10.48550/arXiv.2206.08349

has been cited by the following article:

• TITLE: Dixit Player with Open CLIP

  AUTHORS: Ryan Wei

  KEYWORDS: Computer Vision, AI, CLIP, Dixit, Open AI, Creative Gameplay, Open CLIP, Natural Language Processing, Visual Models, Game AI, Image-Text Pairing

  JOURNAL NAME: Journal of Data Analysis and Information Processing, Vol.11 No.4, November 29, 2023

  ABSTRACT: A computer vision approach through Open AI’s CLIP, a model capable of predicting text-image pairs, is used to create an AI agent for Dixit, a game which requires creative linking between images and text. This paper calculates baseline accuracies for both the ability to match the correct image to a hint and the ability to match up with human preferences. A dataset created by previous work on Dixit is used for testing. CLIP is utilized through the comparison of a hint to multiple images, and previous hints, achieving a final accuracy of 0.5011 which surpasses previous results.