NIST · ИТ · 2ec644954d8cb80265f4
TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime
The TREC Deep Learning (DL) Track studies ad hoc search in the large data regime, meaning that a large set of human-labeled training data is available. Results so far indicate that the best models with large data are likely deep neural networks. This paper
NIST · ИТОфициальный источник · 2021-07-11
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"title_en": "TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime",
"designation": "",
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"date": "2021-07-11",
"date_original": "July 11, 2021",
"url": "https://www.nist.gov/publications/trec-deep-learning-track-reusable-test-collections-large-data-regime",
"source": "NIST Publications",
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"authors_en": "Ellen M. Voorhees , Ian Soboroff , Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos",
"abstract_excerpt_en": "The TREC Deep Learning (DL) Track studies ad hoc search in the large data regime, meaning that a large set of human-labeled training data is available. Results so far indicate that the best models with large data are likely deep neural networks. This paper",
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"title_en": "TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime",
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"date": "2021-07-11",
"date_original": "July 11, 2021",
"url": "https://www.nist.gov/publications/trec-deep-learning-track-reusable-test-collections-large-data-regime",
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"authors_en": "Ellen M. Voorhees , Ian Soboroff , Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos",
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