{"slug": "ynu-hpcc-at-semeval-2025-task-11-bridging-the-gap-in-text-based-emotion-using", "title": "YNU-HPCC at SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Using Multiple Prediction Headers", "summary": "The YNU-HPCC team placed in subtask A of SemEval-2025 Task 11 with a RoBERTa-based system that scored an official ranking score of 0.44 across all languages, according to the team's arXiv paper. The team modified the model's output head to process one emotion at a time and translated the entire dataset into English with Google Translate, finding that a single prediction head outperformed six heads predicting six emotions simultaneously and that training on the uniformly translated English dataset beat the original. The code is available at https://github.com/BGWH123/Semeval-2025-task11.", "body_md": "arXiv:2609.19238v1 Announce Type: new \nAbstract: This paper describes the participation of the YNU-HPCC team in subtask A of task 11, Bridging the Gap in Text-Based Emotion at SemEval-2025. Our best-performing system employs the RoBERTa (Robustly Optimized BERT Approach) model, an improved version of BERT that utilizes the Transformer encoder architecture. We enhanced the output head to allow the model to process one emotion simultaneously. We obtained the official ranking score (0.44), including results from all languages. The entire dataset was translated into English using Google Translate to facilitate subsequent processing. Through probabilistic and attention analyses, we found that (I) a single prediction head performs better than six heads predicting six emotions simultaneously, and (II) training on a uniformly translated English dataset yields better results than using the original dataset. The code is available at: https://github.com/BGWH123/Semeval-2025-task11.", "url": "https://wpnews.pro/news/ynu-hpcc-at-semeval-2025-task-11-bridging-the-gap-in-text-based-emotion-using", "canonical_source": "https://arxiv.org/abs/2609.19238", "published_at": "2026-09-18 04:00:00+00:00", "updated_at": "2026-09-18 04:26:16.297724+00:00", "lang": "en", "topics": ["natural-language-processing", "ai-research", "machine-learning"], "entities": ["YNU-HPCC", "SemEval-2025 Task 11", "RoBERTa", "BERT", "Google Translate", "arXiv"], "alternates": {"html": "https://wpnews.pro/news/ynu-hpcc-at-semeval-2025-task-11-bridging-the-gap-in-text-based-emotion-using", "markdown": "https://wpnews.pro/news/ynu-hpcc-at-semeval-2025-task-11-bridging-the-gap-in-text-based-emotion-using.md", "text": "https://wpnews.pro/news/ynu-hpcc-at-semeval-2025-task-11-bridging-the-gap-in-text-based-emotion-using.txt", "jsonld": "https://wpnews.pro/news/ynu-hpcc-at-semeval-2025-task-11-bridging-the-gap-in-text-based-emotion-using.jsonld"}}