Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks (2022.naacl-main)
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| Challenge: | Existing methods to augment retrieval-augmented generation models with retrievers often rely on spurious cues or generate hallucinations during inference. |
| Approach: | They propose a method to incorporate evidentiality of passages into training a retrieval-augmented generation model. |
| Outcome: | The proposed method outperforms its direct counterpart on all knowledge-intensive tasks. |
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