Document Ranking
57 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
Latest papers
Understanding Performance of Long-Document Ranking Models through Comprehensive Evaluation and Leaderboarding
oaqa/FlexNeuART
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Most other models had poor zero-shot performance (sometimes at a random baseline level) but outstripped MaxP by as much 13-28\% after finetuning.
BERT Rankers are Brittle: a Study using Adversarial Document Perturbations
The aim of our algorithms is to add/replace a small number of tokens to a highly relevant or non-relevant document to cause a large rank demotion or promotion.
CODEC: Complex Document and Entity Collection
We also show that the manual query reformulations significantly improve document ranking and entity ranking performance.
Long Document Re-ranking with Modular Re-ranker
luyug/mores_plus
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In this paper, we propose instead to model full query-to-document interaction, leveraging the attention operation and modular Transformer re-ranker framework.
Socialformer: Social Network Inspired Long Document Modeling for Document Ranking
smallporridge/socialformer
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In this paper, we propose the model Socialformer, which introduces the characteristics of social networks into designing sparse attention patterns for long document modeling in document ranking.
Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models
hltcoe/colbert-x
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These models have improved the effectiveness of retrieval systems well beyond that of lexical term matching models such as BM25.
Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study
Our results also indicate that our reproduced screening prioritisation method, (1) is generalisable across datasets of similar and different topicality compared to the original implementation, (2) that when using multiple seed studies, the effectiveness of the method increases using our techniques to enable this, (3) and that the use of multiple seed studies produces more stable rankings compared to single seed studies.
Siamese BERT-based Model for Web Search Relevance Ranking Evaluated on a New Czech Dataset
seznam/dareczech
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For further research and evaluation, we release DaReCzech, a unique data set of 1. 6 million Czech user query-document pairs with manually assigned relevance levels.
Efficient Neural Ranking using Forward Indexes
In this paper, we propose the Fast-Forward index -- a simple vector forward index that facilitates ranking documents using interpolation of lexical and semantic scores -- as a replacement for contextual re-rankers and dense indexes based on nearest neighbor search.
Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking
daod/coca
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To learn a more robust representation of the user behavior sequence, we propose a method based on contrastive learning, which takes into account the possible variations in user's behavior sequences.
