Papers with TREC COVID Round 1

1 papers
SLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search (2020.emnlp-main)

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Challenge: Existing search methods for COVID-19 are not based on scientific data, but use a neural re-ranking model pre-trained on scientific text.
Approach: They propose a zero-shot ranking algorithm that adapts to COVID-related scientific literature . they use a neural re-ranking model pre-trained on scientific text and filters the target document .
Outcome: The proposed algorithm outperforms models on the TREC COVID Round 1 leaderboard . it outperformed models that do not rely on TREC-COVID data .

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