Papers with question encoder
Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy (C18-1)
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Deepak Gupta, Rajkumar Pujari, Asif Ekbal, Pushpak Bhattacharyya, Anutosh Maitra, Tom Jain, Shubhashis Sengupta
| Challenge: | Existing QA systems that answer factual questions with short answers are rare in practice. |
| Approach: | They propose a proposed two-layered taxonomy technique for semantic question matching . they augment state-of-the-art deep learning models with question classes from a deep learning based question classifier . |
| Outcome: | The proposed technique achieves state-of-the-art on an open-domain dataset. |
Phrase-Indexed Question Answering: A New Challenge for Scalable Document Comprehension (D18-1)
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| Challenge: | Existing QA models rely on learning interaction between document and question . current models require explicit attention to the document before or as it reads it . |
| Approach: | They propose a modular question answering task that enforces complete independence of the document encoder from the question encoder. |
| Outcome: | The proposed model achieves reasonable accuracy but significantly underperforms unconstrained QA models. |