2025
SemEval
SemEval 2025
FiRC-NLP at SemEval-2025 Task 11: To Prompt or to Fine-Tune? Approaches for Multilingual Emotion Classification
Abstract
AbstractIn this paper, we describe our system devel-oped for participation in SemEval-2025 Task11: Bridging the Gap in Text-Based EmotionDetection. We compare three approaches formultilingual, multi-label emotion classification:XLM-R, an ensemble of models (XLM-5), anda prompt-based approach. We evaluate the per-formance of these models across a diverse setof languages, ranging from high-resource tolow-resource languages
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The Questioner
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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
Authors
Topics
Artificial Intelligence > Learning Paradigms > Transfer Learning
Machine Learning > Core Methods > Classification
Deep Learning > Architectures > Transformers
Natural Language Processing > Applications > Text Classification
Machine Learning > Learning Types > Multimodal Learning
Deep Learning > Learning Types > Multi-Label Classification
Deep Learning > Learning Types > Prompt Engineering
Natural Language Processing > Applications > Emotion Detection