MoodShift — RoBERTa+ESA+TF-IDF+FL with LLM Data Augmentation
Novel contribution: LLM-based minority class augmentation via Groq (llama-3.3-70b)
with self-consistency filtering for label fidelity.
Test Accuracy: 0.9265 | Macro F1: 0.8926
Baseline (no augmentation): Acc=0.9235 | F1=0.8831
ICCA 2026 HCI Research — MoodShift Adaptive Chatbot
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