# Duet at TREC 2019 Deep Learning Track

arXiv: https://arxiv.org/abs/1912.04471 · HTML: https://mlsanity.com/paper/1912.04471/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Dec 2019.

## Built on by (most cited first, 1 of 1)

- [Improving Transformer-Kernel Ranking Model Using Conformer and Query Term Independence](https://mlsanity.com/paper/2104.09393/) (2021)

## Abstract (arXiv)

This report discusses three submissions based on the Duet architecture to the Deep Learning track at TREC 2019. For the document retrieval task, we adapt the Duet model to ingest a "multiple field" view of documents---we refer to the new architecture as Duet with Multiple Fields (DuetMF). A second submission combines the DuetMF model with other neural and traditional relevance estimators in a learning-to-rank framework and achieves improved performance over the DuetMF baseline. For the passage retrieval task, we submit a single run based on an ensemble of eight Duet models.