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Found 4 papers, 2 papers with code
Human Preferences as Dueling Bandits
Based on these simulations, one algorithm stands out for its potential.
Can Old TREC Collections Reliably Evaluate Modern Neural Retrieval Models?
Neural retrieval models are generally regarded as fundamentally different from the retrieval techniques used in the late 1990's when the TREC ad hoc test collections were constructed.
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.
Overview of the TREC 2019 deep learning track
The Deep Learning Track is a new track for TREC 2019, with the goal of studying ad hoc ranking in a large data regime.
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