Papers by Yafang Wang
R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling (2021.acl-long)
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| Challenge: | Existing models with stacked layers do not explicitly model hierarchical structure of language understanding. |
| Approach: | They propose a recursive Transformer model based on differentiable CKY style binary trees to emulate hierarchical composition process. |
| Outcome: | The proposed model can predict words given their left and right abstraction nodes. |
Data Augmentation for Multiclass Utterance Classification – A Systematic Study (2020.coling-main)
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| Challenge: | a lack of sufficient training data for some categories can cause imbalanced data distributions . a weak classifier may miscategorize a request, resulting in customer dissatisfaction . |
| Approach: | They propose to use random resampling, word-level transformations and neural text generation to augment existing data to cope with imbalanced data. |
| Outcome: | The proposed methods improve utterance classification results by drawing on utterant variation. |
Query Distillation: BERT-based Distillation for Ensemble Ranking (2020.coling-industry)
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| Challenge: | Recent years have witnessed substantial progress in the development of neural ranking networks, but an increasingly heavy computational burden due to growing numbers of parameters and the adoption of model ensembles. |
| Approach: | They propose a two-stage distillation method that allows a smaller student model to be trained while benefiting from the better performance of the teacher model. |
| Outcome: | The proposed method shows higher-quality rankings compared to the teacher model. |
Interactive Question Clarification in Dialogue via Reinforcement Learning (2020.coling-industry)
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| Challenge: | ambiguous questions are a perennial problem in real-world dialogue systems. |
| Approach: | They propose a reinforcement model to clarify ambiguous questions by suggesting refinements of the original query. |
| Outcome: | The proposed model improves on real-world user clicks and shows significant improvements . it suggests that the original query is refined to clarify ambiguous questions . |