Papers by Marco del Tredici

1 papers
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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