mlsanityData to 14 Oct 2026

A Comparison of Question Rewriting Methods for Conversational Passage Retrieval

arXiv 2101.07382 ↗First posted 19 Jan 2021cs.IR cs.CLcited by 16

Not on the map. Why?

Abstract (arXiv)

Conversational passage retrieval relies on question rewriting to modify the original question so that it no longer depends on the conversation history. Several methods for question rewriting have recently been proposed, but they were compared under different retrieval pipelines. We bridge this gap by thoroughly evaluating those question rewriting methods on the TREC CAsT 2019 and 2020 datasets under the same retrieval pipeline. We analyze the effect of different types of question rewriting methods on retrieval performance and show that by combining question rewriting methods of different types we can achieve state-of-the-art performance on both datasets.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 6 of its 9 references that are in the map. First posted on arXiv 19 Jan 2021.

Builds on

6 of 9 references.

References · 6

  1. 2019Passage Re-ranking with BERTcited by 645
  2. 2020Open-Domain Question Answering Goes Conversational via Question Rewritingcited by 148
  3. 2020Question Rewriting for Conversational Question Answeringcited by 93
  4. 2020Few-Shot Generative Conversational Query Rewritingcited by 85
  5. 2020Query Resolution for Conversational Search with Limited Supervisioncited by 52
  6. 2020Topic Propagation in Conversational Searchcited by 10

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 3; 2023: 3; 2024: 5; 2025: 2; 2026: 2.

16 papers.

Sort:

By area: