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Found 3 papers, 1 papers with code
Effectively Prompting Small-sized Language Models for Cross-lingual Tasks via Winning Tickets
Then, we prepend soft prompts to the original pre-trained language model and only update the selected parameters together with prompt-related parameters when adapting to the downstream tasks.
Multi-level Distillation of Semantic Knowledge for Pre-training Multilingual Language Model
In this paper, we propose Multi-level Multilingual Knowledge Distillation (MMKD), a novel method for improving multilingual language models.
Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography
Experiment results on our clinical MCE data set demonstrate that the neural network trained with the proposed loss function outperforms those existing ones that try to obtain a unique ground truth from multiple annotations, both quantitatively and qualitatively.
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