2025
SEMEVAL
SemEval 2025
YNU-HPCC at SemEval-2025 Task 2: Local Cache and Online Retrieval-Based method for Entity-Aware Machine Translation
Abstract
AbstractThis paper presents methods for {textbf{SemEval-2025 Task 11}} on text-based emotion detection across three tracks: Multi-label Emotion Detection, Emotion Intensity Prediction, and Cross-lingual Emotion Detection. We apply approaches such as supervised fine-tuning, preference-based reinforcement learning, and few-shot learning to enhance performance. Our combined strategies result in improved accuracy, particularly in multi-label and cross-lingual emotion detection, demonstrating the effectiveness of these methods in diverse linguistic settings.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
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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
Topics
Artificial Intelligence > Learning Paradigms > Few-Shot Learning
Machine Learning > Learning Types > Self-Supervised Learning
Machine Learning > Learning Types > Few-Shot Learning
Natural Language Processing > Generation > Machine Translation
Machine Learning > Learning Types > Retrieval-Augmented Generation