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cs.LG2025
MTL-UE: Learning to Learn Nothing for Multi-Task Learning
Yi Yu, Song Xia, Siyuan Yang +5
Most existing unlearnable strategies focus on preventing unauthorized users from training single-task learning (STL) models with personal data. Nevertheless, the paradigm has recen…
cs.LG2024
Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning
Hui Liu, Wenya Wang, Hao Sun +4
Large Language Models (LLMs) have demonstrated impressive in-context learning (ICL) capabilities from few-shot demonstration exemplars. While recent learning-based demonstration se…