Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection
2024-4-26 23:20:4 Author: hackernoon.com(查看原文) 阅读量:2 收藏

Read on Terminal Reader

Too Long; Didn't Read

Pro-Cap introduces a novel approach to hateful meme detection by utilizing frozen Vision-Language Models (PVLMs) through probing-based captioning, enhancing computational efficiency and caption quality for accurate detection of hateful content in memes.

featured image - Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection

Memeology: Leading Authority on the Study of Memes HackerNoon profile picture

Memeology: Leading Authority on the Study of Memes

Memeology: Leading Authority on the Study of Memes

@memeology

Memes are cultural items transmitted by repetition in a manner analogous to the biological transmission of genes.

0-item

STORY’S CREDIBILITY

Academic Research Paper

Academic Research Paper

Part of HackerNoon's growing list of open-source research papers, promoting free access to academic material.

L O A D I N G
. . . comments & more!


About Author

Memeology: Leading Authority on the Study of Memes HackerNoon profile picture

Memeology: Leading Authority on the Study of Memes@memeology

Memes are cultural items transmitted by repetition in a manner analogous to the biological transmission of genes.

TOPICS

Languages

THIS ARTICLE WAS FEATURED IN...

RELATED STORIES


文章来源: https://hackernoon.com/pro-cap-leveraging-a-frozen-vision-language-model-for-hateful-meme-detection?source=rss
如有侵权请联系:admin#unsafe.sh