2025
EMNLP
EMNLP 2025
taskGen at TSAR 2025 Shared Task Exploring prompt strategies with linguistic knowledge
Abstract
AbstractTaskGen ranked as 6th best team in the TSAR 2025 shared task for English text adaptation to a target CEFR level. Our experiments consisted of prompting a Llama-3.1-8B-Instruct model with linguistic descriptors of the target level, examples of adaptations and multi-step approaches. Our best run, 13th in the overall ranking, applied an ensemble strategy using a voting mechanism to find the most adequate among 10 texts, each produced by a different prompting strategy.
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
🧭
Keyword Pioneer
— linguistic descriptor
🐝
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