Neural Ranking with Weak Supervision for Open-Domain Question Answering : A Survey (2023.findings-eacl)
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| Challenge: | Neural ranking models require substantial amounts of relevance annotations, which is costly to scale. |
| Approach: | They propose to train a NR model with weak supervision instead of annotations . they use a structured overview of standard WS signals used for training a model . |
| Outcome: | The proposed approach reduces the cost of annotations by using weak supervision instead of a parametric model. |
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