ICT-NLP at SemEval-2026 Task 3: Less Is More -- Multilingual Encoder with Joint Training and Adaptive Ensemble for Dimensional Aspect Sentiment Regression
Researchers from ICT-NLP have developed a novel system for dimensional aspect sentiment regression, achieving top rankings in the SemEval-2026 Task 3. Their approach utilizes a multilingual encoder with joint training and an adaptive ensemble, eschewing large language models for efficiency. This method demonstrated strong cross-lingual transfer capabilities and improved training stability, leading to high performance across multiple datasets. AI
IMPACT Presents a novel, efficient approach to sentiment analysis that could inform future research in multilingual NLP.