Papers with adaptive pre-training
KALA: Knowledge-Augmented Language Model Adaptation (2022.naacl-main)
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| Challenge: | Pre-trained language models (PLMs) have proved to be effective on various natural language understanding tasks. |
| Approach: | They propose a domain adaption framework which modulates the intermediate hidden representations of PLMs with domain knowledge, consisting of entities and their relational facts. |
| Outcome: | The proposed framework outperforms adaptive pre-training on question answering and named entity recognition tasks on multiple datasets across different domains. |
Chinese Automatic Readability Assessment Using Adaptive Pre-training and Linguistic Feature Fusion (2025.coling-main)
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| Challenge: | Existing methods for classification of reading difficulty of texts are insufficiently trained and lack of linguistic features. |
| Approach: | They propose a method that combines adaptive pre-training with feature fusion to capture different text difficulties and an interactive attention mechanism to integrate linguistic and deep features. |
| Outcome: | The proposed method achieves state-of-the-art (SOTA) performance on Chinese textbook dataset and can be applied to other languages. |