Unimodal Training for Multimodal Meme Sentiment Classification: Hyperparameters and Settings

Written by @memeology | Published on 2024-04-07T23:42:13.430Z

TL;DR →

This study introduces a novel approach, using unimodal training to enhance multimodal meme sentiment classifiers, significantly improving performance and efficiency in meme sentiment analysis.

Authors:

(1) Muzhaffar Hazman, University of Galway, Ireland;

(2) Susan McKeever, Technological University Dublin, Ireland;

(3) Josephine Griffith, University of Galway, Ireland.

Table of Links

Abstract and Introduction

Related Works

Methodology

Results

Limitations and Future Works

Conclusion, Acknowledgments, and References

A Hyperparameters and Settings

B Metric: Weighted F1-Score

C Architectural Details

D Performance Benchmarking

E Contingency Table: Baseline vs. Text-STILT

A Hyperparameters and Settings

This paper is available on arxiv under CC 4.0 license.

Written by

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

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