2025
SemEval
SemEval 2025
Empaths at SemEval-2025 Task 11: Retrieval-Augmented Approach to Perceived Emotions Prediction
Abstract
AbstractThe paper introduces EmoRAG, a retrieval-augmented emotion detection system designed for the SemEval-2025 Task 11. It uses an ensemble of models, retrieving similar examples to prompt large language models (LLMs) for emotion predictions. The retriever component fetches the most relevant examples from a database, which are then used as few-shot prompts for the models. EmoRAG achieves strong, scalable performance across languages with no training at all, demonstrating effectiveness in both high and low-resource languages.
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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
Topics
Artificial Intelligence > Learning Paradigms > Few-Shot Learning
Natural Language Processing > Resources & Methods > Large Language Models
Natural Language Processing > Applications > Sentiment Analysis
Artificial Intelligence > Core AI > Large Language Models
Natural Language Processing > Generation > Retrieval-Augmented Generation
Natural Language Processing > Applications > Emotion Detection