Papers by Chunping Ma
Hierarchy-Aware Global Model for Hierarchical Text Classification (2020.acl-main)
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| Challenge: | Existing methods for hierarchical text classification are limited and lack holistic structural information. |
| Approach: | They propose a hierarchy-aware global model with two variants that learn hierarchy-based label embeddings through an encoder and conduct inductive fusion of label-alike text features. |
| Outcome: | The proposed model improves on three benchmark datasets. |
Robust Self-Augmentation for Named Entity Recognition with Meta Reweighting (2022.naacl-main)
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| Challenge: | Prior research has focused on reducing noise for specific methods to achieve an effective integration. |
| Approach: | They propose to use token substitution and mixup to improve named entity recognition (NER) using a meta-reweighting strategy, which is extensible and requires little effort. |
| Outcome: | The proposed method is extensible, imposing little effort on a specific self-augmentation method. |
Counterfactual Inference for Text Classification Debiasing (2021.acl-long)
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| Challenge: | Existing methods to capture unintended dataset biases are expensive and require elaborate balancing strategies. |
| Approach: | They propose a model-agnostic text classification debiasing framework which can effectively avoid employing data manipulations or designing balancing mechanisms. |
| Outcome: | The proposed framework can effectively avoid data manipulations or designing balancing mechanisms to capture unintended dataset biases. |