Papers by Liang Guanqing
Improving Model Generalization: A Chinese Named Entity Recognition Case Study (2021.acl-short)
Copied to clipboard
| Challenge: | Named Entity Recognition (NER) is a fundamental building block for various downstream natural language processing tasks due to the ambiguous word boundaries and complex composition. |
| Approach: | They propose to resample entities within the same category to encourage a model to leverage both name and context knowledge in the training process. |
| Outcome: | The proposed method significantly improves a model’s ability to detect unseen entities, especially for company, organization and position categories. |
A Comparative Study of Faithfulness Metrics for Model Interpretability Methods (2022.acl-long)
Copied to clipboard
| Challenge: | Existing methods to reveal the reasoning processes of machine learning models are difficult to interpret due to their complexity. |
| Approach: | They propose to use diagnosticity and complexity to assess faithfulness of machine learning models . they propose to apply posthoc interpretation methods to reveal reasoning behind models based on internal reasoning . |
| Outcome: | The proposed interpretation metrics show conflicting preferences when comparing interpretations . sufficiency and comprehensiveness metrics have higher diagnosticity and lower complexity . |