Papers with generative step
Data Programming for Learning Discourse Structure (P19-1)
Copied to clipboard
| Challenge: | Discourse structures are a relational semantic structure that convey causal, topical, argumentative relations or more generally coherence relations. |
| Approach: | They propose to use Snorkel to label training data using expert-composed heuristics and transform them into probability distributions of the class labels given to training candidates. |
| Outcome: | The proposed paradigm can be used for difficult tasks such as that of discourse attachment. |
Weak Supervision for Learning Discourse Structure (D19-1)
Copied to clipboard
| Challenge: | a weak supervision approach is a promising tool for learning discourse structure for multi-party dialogue. |
| Approach: | They propose a data programming paradigm that allows a user to label training data using expert-composed heuristics and transform them into probability distributions of the class labels. |
| Outcome: | The proposed approach outperforms both deep learning and traditional ML approaches on the task of learning discourse structure for multi-party dialogue. |