| Challenge: | Existing approaches to index, retrieve, and read documents as evidence suffer from large computational overheads. |
| Approach: | They propose an encoder-decoder framework with an entity memory that stores entity knowledge as latent representations and pre-trained on Wikipedia along with encoder parameters. |
| Outcome: | The proposed framework outperforms memory-based and non-memory encoder-decoder models on various entity-intensive question answering and generation tasks. |
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| Challenge: | Entity Disambiguation (ED) is a crucial problem in Natural Language Processing (NLP). |
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ExtEnD: Extractive Entity Disambiguation (2022.acl-long)
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| Challenge: | Entity disambiguation (ED) is a task in natural language processing that requires a large pre-trained language model to perform. |
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