Document Ranking
58 papers with code • 2 benchmarks • 6 datasets
Sort documents according to some criterion so that the "best" results appear early in the result list displayed to the user (Source: Wikipedia).
Benchmarks
These leaderboards are used to track progress in Document Ranking
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Libraries
Use these libraries to find Document Ranking models and implementations
CLUE
Qulac
Most implemented papers
HARE: a Flexible Highlighting Annotator for Ranking and Exploration
OSU-slatelab/HARE
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IJCNLP 2019
Exploration and analysis of potential data sources is a significant challenge in the application of NLP techniques to novel information domains.
TU Wien @ TREC Deep Learning '19 -- Simple Contextualization for Re-ranking
The usage of neural network models puts multiple objectives in conflict with each other: Ideally we would like to create a neural model that is effective, efficient, and interpretable at the same time.
Cross-lingual Information Retrieval with BERT
Multiple neural language models have been developed recently, e. g., BERT and XLNet, and achieved impressive results in various NLP tasks including sentence classification, question answering and document ranking.
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations
Deep pretrained transformer networks are effective at various ranking tasks, such as question answering and ad-hoc document ranking.
Local Self-Attention over Long Text for Efficient Document Retrieval
sebastian-hofstaetter/transformer-kernel-ranking
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In this work, we propose a local self-attention which considers a moving window over the document terms and for each term attends only to other terms in the same window.
GLOW : Global Weighted Self-Attention Network for Web Search
cadobe/bison
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Deep matching models aim to facilitate search engines retrieving more relevant documents by mapping queries and documents into semantic vectors in the first-stage retrieval.
Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering
We extend the ranked retrieval annotations of the Deep Learning track of TREC 2019 with passage and word level graded relevance annotations for all relevant documents.
PARADE: Passage Representation Aggregation for Document Reranking
canjiali/PARADE
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In this work, we explore strategies for aggregating relevance signals from a document's passages into a final ranking score.
Longformer for MS MARCO Document Re-ranking Task
Two step document ranking, where the initial retrieval is done by a classical information retrieval method, followed by neural re-ranking model, is the new standard.
Long Document Ranking with Query-Directed Sparse Transformer
hallogameboy/QDS-Transformer
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Findings of the Association for Computational Linguistics 2020
In this paper, we design Query-Directed Sparse attention that induces IR-axiomatic structures in transformer self-attention.
