Papers by Shudi Hou
Promoting Pre-trained LM with Linguistic Features on Automatic Readability Assessment (2022.aacl-short)
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| Challenge: | Automatic readability assessment (ARA) aims at classifying the readability level of a text automatically. |
| Approach: | They propose to integrate linguistic features with pre-trained language models to improve the accuracy of ARA. |
| Outcome: | The proposed algorithm improves on the long passage characteristic of ARA using commonly used linguistic features and abundant datasets. |
Contrastive Bootstrapping for Label Refinement (2023.acl-short)
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| Challenge: | Existing methods for fine-grained classification categorize texts into coarse-gritty classes, but they are suboptimal in real-world scenarios. |
| Approach: | They propose a lightweight contrastive clustering-based bootstrapping method to iteratively refine the labels of passages. |
| Outcome: | The proposed method outperforms the state-of-the-art methods by a large margin on NYT and 20News datasets. |