Papers by Andre Cianflone
Attention for Implicit Discourse Relation Recognition (L18-1)
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| Challenge: | Existing approaches to implicit discourse relation recognition reach F1 scores of 9.95% to 37.67% . a neural network exploits the strong correlation between pairs of words that implicitly signal a discourse relation. |
| Approach: | They propose a neural network which exploits strong correlation between pairs of words . they use an encoder-decoder model with attention to detect a latent discourse relation . |
| Outcome: | The proposed model outperforms state-of-the-art models on fine-grained classification and fine-granular classification while computing parameters without pooling and fully connected layers. |
Let’s do it “again”: A First Computational Approach to Detecting Adverbial Presupposition Triggers (P18-1)
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| Challenge: | a novel task of predicting adverbial presupposition triggers is useful for natural language generation . a focus is on a new attention mechanism for predicting presuposition trigger . |
| Approach: | They propose a new attention mechanism for predicting adverbial presupposition triggers . they propose to augment a baseline neural network without additional trainable parameters . |
| Outcome: | The proposed model outperforms baseline models in predicting adverbial presupposition triggers. |