BERT-QE
ranking
BERT-QE | ranking | |
---|---|---|
1 | 1 | |
48 | 2,714 | |
- | 0.1% | |
0.0 | 6.3 | |
over 2 years ago | about 2 months ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
BERT-QE
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[D] BERT-QE: Contextualized Query Expansion for Document Re-ranking (Research Paper Walkthrough)
⏩ Paper Title: BERT-QE: Contextualized Query Expansion for Document Re-ranking ⏩ Paper: https://arxiv.org/pdf/2009.07258.pdf ⏩ Code: https://github.com/zh-zheng/BERT-QE ⏩ Author: Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, Andrew Yates ⏩ Organisation: University of Chinese Academy of Sciences, Amazon Alexa, Institute of Software, Chinese Academy of Sciences, Max Planck Institute for Informatics
ranking
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[D] learning to Rank
There are many different models and loss functions used for ranking (Tensorflow Ranking offers a bunch, probably also available for Jax / Pytorch / etc., or easily convertible).
What are some alternatives?
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