REANO: Optimising Retrieval-Augmented Reader Models through Knowledge Graph Generation (2024.acl-long)
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| Challenge: | Existing knowledge graphs suffer from incompleteness and lack information critical for answering given questions. |
| Approach: | They propose to enhance the open domain question answering model with a knowledge graph generation module that generates KGs from the passages and an answer predictor. |
| Outcome: | The proposed model improves the exact match score by 2.7% on the EntityQuestion dataset, with an average improvement of 1.8% across all the datasets. |
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