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Research Paper#AI, Depression Detection, Memes, LLM, Multi-Agent Systems🔬 ResearchAnalyzed: Jan 3, 2026 06:14

MAMAMemeia: Meme-Based Depression Detection

Published:Dec 31, 2025 18:06
1 min read
ArXiv

Analysis

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.
Reference

“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.”

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Research#mental health🔬 ResearchAnalyzed: Jan 4, 2026 10:08

QuanvNeXt: An end-to-end quanvolutional neural network for EEG-based detection of major depressive disorder

Published:Dec 10, 2025 10:44
1 min read
ArXiv

Analysis

This article introduces a novel approach using quanvolutional neural networks (QNNs) for detecting major depressive disorder (MDD) based on electroencephalogram (EEG) data. The use of QNNs, a relatively new area, suggests potential advancements in the field of mental health diagnosis. The focus on EEG data is also significant, as it offers a non-invasive method for assessing brain activity. The article's publication on ArXiv indicates it's a pre-print, suggesting ongoing research and potential for future peer review and refinement.
Reference

“The article focuses on using quanvolutional neural networks (QNNs) for EEG-based detection of major depressive disorder.”

PermalinkArXiv