Mitigating Data Scarcity in Psychological Defense Classification with Context-Aware Synthetic Augmentation · DeepSignal
Mitigating Data Scarcity in Psychological Defense Classification with Context-Aware Synthetic Augmentation arXiv cs.CL · Hoang-Thuy-Duong Vu, Quoc-Cuong Pham, Huy-Hieu Pham 2d ago · · · · A context-aware synthetic augmentation framework improves psychological defense mechanism classification despite data scarcity.
Key Points Hybrid model combines contextual language and clinical features. Achieves 58.26% accuracy and 24.62% macro-F1 score. Source code available on GitHub. Reader Mode unavailable (could not extract clean content).
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📰 Read Original Signal Score
Moderate signal — interesting but narrower impact.
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Source authority 20% 80
Community heat 20% 0
Technical impact 30%
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≥75 high · 50–74 medium · <50 low
Why Featured
This framework addresses data scarcity in psychological defense classification, enabling developers and PMs to enhance AI models and investors to identify innovative solutions in mental health applications.