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Passage re-ranking is the task of scoring and re-ranking a collection of retrieved documents based on an input query.

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Greatest papers with code

Document Expansion by Query Prediction

17 Apr 2019castorini/Anserini

One technique to improve the retrieval effectiveness of a search engine is to expand documents with terms that are related or representative of the documents' content. From the perspective of a question answering system, this might comprise questions the document can potentially answer.

PASSAGE RE-RANKING QUESTION ANSWERING

Passage Re-ranking with BERT

13 Jan 2019nyu-dl/dl4marco-bert

Recently, neural models pretrained on a language modeling task, such as ELMo (Peters et al., 2017), OpenAI GPT (Radford et al., 2018), and BERT (Devlin et al., 2018), have achieved impressive results on various natural language processing tasks such as question-answering and natural language inference.

Ranked #2 on Passage Re-Ranking on MS MARCO (using extra training data)

PASSAGE RE-RANKING

An Updated Duet Model for Passage Re-ranking

18 Mar 2019dfcf93/MSMARCO

We propose several small modifications to Duet---a deep neural ranking model---and evaluate the updated model on the MS MARCO passage ranking task.

PASSAGE RE-RANKING

Mitigating the Position Bias of Transformer Models in Passage Re-Ranking

18 Jan 2021sebastian-hofstaetter/transformer-kernel-ranking

In this work we analyze position bias on datasets, the contextualized representations, and their effect on retrieval results.

PASSAGE RE-RANKING QUESTION ANSWERING TRANSFER LEARNING