Passage Re-Ranking

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

19 shown of 19 papers with code (32 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Passage Re-ranking with BERT
  13 Jan 2019 6 repositories listed Syntology ran 2 of 13 samples · 11 unverified
  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…
• Document Expansion by Query Prediction
  17 Apr 2019 5 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  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.
• Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-Ranking
  13 May 2024 2 repositories listed
  Cross-encoders distilled from large language models (LLMs) are often more effective re-rankers than cross-encoders fine-tuned on manually labeled data.
• Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders
  10 Apr 2024 2 repositories listed
  Existing cross-encoder models can be categorized as pointwise, pairwise, or listwise.
• Few-shot Reranking for Multi-hop QA via Language Model Prompting
  25 May 2022 2 repositories listed
  To alleviate the need for a large number of labeled question-document pairs for retriever training, we propose PromptRank, which relies on large language models prompting for multi-hop path reranking.
• Dealing with Typos for BERT-based Passage Retrieval and Ranking
  27 Aug 2021 2 repositories listed
  Our experimental results on the MS MARCO passage ranking dataset show that, with our proposed typos-aware training, DR and BERT re-ranker can become robust to typos in queries, resulting in significantly improved…
• Exploring the Effectiveness of Multi-stage Fine-tuning for Cross-encoder Re-rankers
  28 Mar 2025 1 repository listed
  State-of-the-art cross-encoders can be fine-tuned to be highly effective in passage re-ranking.
• Multi-Granularity Guided Fusion-in-Decoder
  3 Apr 2024 1 repository listed
  In Open-domain Question Answering (ODQA), it is essential to discern relevant contexts as evidence and avoid spurious ones among retrieved results.
• Adapting Language Models to Compress Contexts
  24 May 2023 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  Transformer-based language models (LMs) are powerful and widely-applicable tools, but their usefulness is constrained by a finite context window and the expensive computational cost of processing long text documents.
• Improving Conversational Passage Re-ranking with View Ensemble
  26 Apr 2023 1 repository listed
  This paper presents ConvRerank, a conversational passage re-ranker that employs a newly developed pseudo-labeling approach.
• T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
  7 Apr 2023 1 repository listed
  T2Ranking comprises more than 300K queries and over 2M unique passages from real-world search engines.
• HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer Reranking
  21 May 2022 1 repository listed
  Existing text retrieval systems with state-of-the-art performance usually adopt a retrieve-then-reranking architecture due to the high computational cost of pre-trained language models and the large corpus size.
• RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking
  14 Oct 2021 1 repository listed
  In this paper, we propose a novel joint training approach for dense passage retrieval and passage re-ranking.
• Fast Passage Re-ranking with Contextualized Exact Term Matching and Efficient Passage Expansion
  19 Aug 2021 1 repository listed
  BERT-based information retrieval models are expensive, in both time (query latency) and computational resources (energy, hardware cost), making many of these models impractical especially under resource constraints.
• A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
  25 Jun 2021 1 repository listed
  In contrast to the matching paradigm, the probabilistic nature of generative rankers readily offers a fine-grained measure of uncertainty.
• Exploiting Sentence-Level Representations for Passage Ranking
  14 Jun 2021 1 repository listed
  Recently, pre-trained contextual models, such as BERT, have shown to perform well in language related tasks.
• Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers
  28 Apr 2021 1 repository listed
  In this work, we first provide a novel framework to measure the fairness in the retrieved text contents of ranking models.
• Mitigating the Position Bias of Transformer Models in Passage Re-Ranking
  18 Jan 2021 1 repository listed
  In this work we analyze position bias on datasets, the contextualized representations, and their effect on retrieval results.
• An Updated Duet Model for Passage Re-ranking
  18 Mar 2019 1 repository listed
  We propose several small modifications to Duet---a deep neural ranking model---and evaluate the updated model on the MS MARCO passage ranking task.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.