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TextGram: Towards a better domain-adaptive pretraining
Thus, it is important that we select the correct data in the form of domain-specific data from this vast corpus to achieve optimum results aligned with our domain-specific tasks.
Towards Simple and Efficient Task-Adaptive Pre-training for Text Classification
This step helps cover the target domain vocabulary and improves the model performance on the downstream task.
On Sensitivity of Deep Learning Based Text Classification Algorithms to Practical Input Perturbations
In this work, we carry out a data-focused study evaluating the impact of systematic practical perturbations on the performance of the deep learning based text classification models like CNN, LSTM, and BERT-based algorithms.
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