Recently, prompt tuning has been widely applied to stimulate the rich knowledge in pre-trained language models (PLMs) serve NLP tasks. Although achieved promising results on some few-class classification tasks, such as sentiment and natural inference, manually designing prompts is cumbersome. Meanwhile, generating automatically also difficult time-consuming. Therefore, obtaining effective for c...

Deep neural networks provide good performance on classification tasks such as those for image, audio, and text classification. However, are vulnerable to adversarial examples. An example is a sample created by adding small noise an original data in way that it will be correctly classified human but misclassified deep network. Studies examples have focused mainly the image field, research expand...

In this paper, we present our progress in pre-training monolingual Transformers for Czech and contribute to the research community by releasing models public. The need such emerged from effort employ language-specific tasks, but found performance of published multilingual be very limited. Since are usually pre-trained 100+ languages, most low-resourced languages (including Czech) under-represen...