Papers by Nikos Voskarides
Performance-Efficiency Trade-Offs in Adapting Language Models to Text Classification Tasks (2022.aacl-short)
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| Challenge: | Pre-trained language models (LMs) are state-of-the-art when adapted to text classification tasks. |
| Approach: | They compare fine-tuning, prompting, and knowledge distillation procedures to train pre-trained language models to downstream tasks. |
| Outcome: | The proposed training procedures perform better when trained with fine-tuning or prompting on large train sets than when trained by prompting or fine-untun. |