Papers by Ygor Gallina

2 papers
Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness (2021.naacl-main)

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Challenge: Neural keyphrase generation models can output absent keyphrases, which are keyphrase that do not appear in the source text.
Approach: They propose a finer-grained categorization scheme that sheds more light on the impact of absent keyphrases on scientific document retrieval.
Outcome: The proposed model shows that only 20% of the words that make up keyphrases actually serve as document expansion, but this small fraction behind much of the gains observed in retrieval effectiveness.
Keyphrase Generation for Scientific Document Retrieval (2020.acl-main)

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Challenge: Sequence-to-sequence models have been used to generate keyphrases, but it is unclear whether they are reliable enough for document retrieval.
Approach: They propose a framework for extrinsic evaluation that allows for a better understanding of the limitations of keyphrase generation models.
Outcome: The proposed models improve retrieval performance by supplementing documents with keyphrases that are not present in the source text and generalizing models across domains.

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