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20222026
most citedFew-shot learning for automated content analysis: Efficient coding of arguments and claims in the debate on arms deliveries to Ukraine

2 citations · 4 across the 3 of their papers we have counts for

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cs.CL2024

PETapter: Leveraging PET-style classification heads for modular few-shot parameter-efficient fine-tuning

Jonas Rieger, Mattes Ruckdeschel, Gregor Wiedemann

Few-shot learning and parameter-efficient fine-tuning (PEFT) are crucial to overcome the challenges of data scarcity and ever growing language model sizes. This applies in particul…