Overview of the TREC 2021 deep learning track
Microsoft (United States) · University College London · +1 more institution
Abstract
This is the fifth year of the TREC Deep Learning track. As in previous years, we leverage the MS MARCO datasets that made hundreds of thousands of human-annotated training labels available for both passage and document ranking tasks. We mostly repeated last year's design, to get another matching test set, based on the larger, cleaner, less-biased v2 passage and document set, with passage ranking as primary and document ranking as a secondary task (using labels inferred from passage). As we did last year, we sample from MS MARCO queries that were completely held out, unused in corpus construction, unlike the test queries in the first three years. This approach yields a more difficult test with more headroom for…
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Authors
8- NCNick CraswellCorresponding
Microsoft (United States)
- BMBhaskar Mitra
Microsoft (United States)
- EYEmine Yılmaz
University College London
- DCDaniel Campos
Microsoft (United States)
- CDCampos, Daniel
National Institute of Standards and Technology
Topics & keywords
- Computer science
- Pooling
- Ranking (information retrieval)
- Deep learning
- Test set
- Artificial intelligence
- Task (project management)
- Training set