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.
🌉
Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
Authors
Topics
Artificial Intelligence > Learning Paradigms > Few-Shot Learning
Machine Learning > Learning Types > Self-Supervised Learning
Natural Language Processing > Applications > Machine Translation
Machine Learning > Learning Types > Few-Shot Learning
Machine Learning > Learning Types > Retrieval-Augmented Generation