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2025 ACL ACL 2025

UB_Tel-U at SemEval-2025 Task 11: Emotions Without Borders - A Unified Framework for Multilingual Classification Using Augmentation and Ensemble

Abstract

AbstractIn this SemEval 2025 Task 11 paper, we tackled three tracks: Multi-label Emotion Detection, Emotion Intensity, and Cross-lingual Emotion Detection. Our approach harnesses diverse external corpora and robust data augmentation techniques across Spanish, English, and Arabic, enhancing both the diversity and resilience of the dataset. Instead of developing separate models for each language, we merge the data into a unified multilingual dataset, enabling our model to learn cross-lingual patterns and relationships simultaneously. Our ensemble architecture integrates the multilingual strengths of XLM-RoBERTa, a zero-shot classification capability via LLaMA 3, and a specialized pretrained model fine-tuned on English emotion classification. Notably, our system achieved strong performance, ranking 13th for Afrikaans (afr) in Track A, 13th for Amharic (amh) in Track B, and 4th for Hindi (hin) in Track C.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Deep Learning and Machine Learning
🧭 Keyword Pioneer — xlm-roberta classification
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Tirana Noor Fatyanosa , Putra Pandu Adikara , Rochmanu Purnomohadi Erfitra , Muhammad Rajendra Alkautsar Dikna , Sari Dewi Budiwati , Cahyana

Topics

Artificial Intelligence > Core AI > Multimodal Learning Artificial Intelligence > Learning Paradigms > Transfer Learning Machine Learning > Core Methods > Classification Machine Learning > Learning Types > Continual Learning Machine Learning > Learning Types > Self-Supervised Learning Machine Learning > Learning Types > Semi-Supervised Learning Machine Learning > Learning Types > Zero-Shot Learning Machine Learning > Application Areas > Data Augmentation Machine Learning > Application Areas > Domain Adaptation Deep Learning > Architectures > Transformers Deep Learning > Techniques > Model Architecture Deep Learning > Techniques > Pretraining Machine Learning > Learning Types > Multi-Agent Systems Machine Learning > Learning Types > Ensemble Learning Deep Learning > Models > Transformers

Keywords

ensemble learning data augmentation cross-lingual transfer emotion detection ensemble method zero-shot classification pretrained model emotion classification cross-lingual learning multilingual model multilingual classification multilingual emotion transformer model cross-lingual emotion detection xlm-roberta classification
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