MAMAMemeia: Meme-Based Depression Detection
Research Paper#AI, Depression Detection, Memes, LLM, Multi-Agent Systems🔬 Research|Analyzed: Jan 3, 2026 06:14•
Published: Dec 31, 2025 18:06
•1 min read
•ArXivAnalysis
This paper addresses the important and timely problem of identifying depressive symptoms in memes, leveraging LLMs and a multi-agent framework inspired by Cognitive Analytic Therapy. The use of a new resource (RESTOREx) and the significant performance improvement (7.55% in macro-F1) over existing methods are notable contributions. The application of clinical psychology principles to AI is also a key aspect.
Key Takeaways
- •Proposes MAMAMemeia, a multi-agent framework for detecting depressive symptoms in memes.
- •Introduces RESTOREx, a new resource for meme-based depression detection.
- •Achieves a significant performance improvement over existing methods.
- •Applies Cognitive Analytic Therapy (CAT) principles to the AI framework.
Reference / Citation
View Original"MAMAMemeia improves upon the current state-of-the-art by 7.55% in macro-F1 and is established as the new benchmark compared to over 30 methods."