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 with no code
Fusion-in-T5: Unifying Document Ranking Signals for Improved Information Retrieval
Common IR pipelines are typically cascade systems that may involve multiple rankers and/or fusion models to integrate different information step-by-step.
Generative and Pseudo-Relevant Feedback for Sparse, Dense and Learned Sparse Retrieval
Pseudo-relevance feedback (PRF) is a classical approach to address lexical mismatch by enriching the query using first-pass retrieval.
A Static Pruning Study on Sparse Neural Retrievers
Sparse neural retrievers, such as DeepImpact, uniCOIL and SPLADE, have been introduced recently as an efficient and effective way to perform retrieval with inverted indexes.
Noise-Robust Dense Retrieval via Contrastive Alignment Post Training
The success of contextual word representations and advances in neural information retrieval have made dense vector-based retrieval a standard approach for passage and document ranking.
CREDENCE: Counterfactual Explanations for Document Ranking
Towards better explainability in the field of information retrieval, we present CREDENCE, an interactive tool capable of generating counterfactual explanations for document rankers.
An Empirical Study of Uniform-Architecture Knowledge Distillation in Document Ranking
Specifically, when the student models are in cross-encoder architecture, a pairwise loss of hard labels is critical for training student models, whereas the distillation objectives of intermediate Transformer layers may hurt performance.
Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillation
Moreover, unlike the English-to-English retrieval task, where large-scale training collections for document ranking such as MS MARCO are available, the lack of cross-lingual retrieval data for low-resource language makes it more challenging for training cross-lingual retrieval models.
Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search
An empirical analysis compares how effective neural methods compare to traditional methods for this task.
Explainability of Text Processing and Retrieval Methods: A Critical Survey
This article provides a broad overview of research on the explainability and interpretability of natural language processing and information retrieval methods.
Query-Specific Knowledge Graphs for Complex Finance Topics
This workshop paper discusses automating the construction of query-specific document and entity knowledge graphs (KGs) for complex research topics.
