Team Unibuc - NLP at SemEval 2025 Task 11: Few-shot text-based emotion detection

This paper describes the approach of the Unibuc - NLP team in tackling the SemEval 2025 Workshop, Task 11: Bridging the Gap in Text-Based Emotion Detection. We mainly focused on experiments using large language models (Gemini, Qwen, DeepSeek) with ei- ther few-shot prompting or fine-tuning. With our final system, for the multi-label emotion detection track (track A), we got an F1-macro of 0.7546 (26/96 teams) for the English sub- set, 0.1727 (35/36 teams) for the Portuguese (Mozambican) subset and 0.325 (1/31 teams) for the Emakhuwa subset.