SOTAVerified

Document Ranking

Sort documents according to some criterion so that the "best" results appear early in the result list displayed to the user (Source: Wikipedia).

Papers

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Showing 26–50 of 168 papers

TitleStatusHype
Recency Ranking by Diversification of Result Set—0
Data Augmentation for Sample Efficient and Robust Document Ranking—0
Evaluating Generative Ad Hoc Information Retrieval—0
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document RankingCode1
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language ModelsCode2
Personalized Search Via Neural Contextual Semantic Relevance Ranking—0
Context Aware Query Rewriting for Text Rankers using LLM—0
Hybrid Retrieval and Multi-stage Text Ranking Solution at TREC 2022 Deep Learning Track—0
GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval—0
Fusion-in-T5: Unifying Document Ranking Signals for Improved Information RetrievalCode0
Generative and Pseudo-Relevant Feedback for Sparse, Dense and Learned Sparse Retrieval—0
A Static Pruning Study on Sparse Neural Retrievers—0
Noise-Robust Dense Retrieval via Contrastive Alignment Post Training—0
Pretraining De-Biased Language Model with Large-scale Click Logs for Document RankingCode1
CREDENCE: Counterfactual Explanations for Document Ranking—0
An Empirical Study of Uniform-Architecture Knowledge Distillation in Document Ranking—0
Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillation—0
Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search—0
Explainability of Text Processing and Retrieval Methods: A Critical Survey—0
LEAD: Liberal Feature-based Distillation for Dense Retrieval—0
Principled Multi-Aspect Evaluation Measures of RankingsCode0
Query-Specific Knowledge Graphs for Complex Finance Topics—0
Enhancing User Behavior Sequence Modeling by Generative Tasks for Session SearchCode0
From Easy to Hard: A Dual Curriculum Learning Framework for Context-Aware Document RankingCode1
Supervised Contrastive Learning Approach for Contextual Ranking—0
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All datasetsDaReCzechClueWeb09-B

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Query-doc RobeCzech (Roberta-base)P@1046.73—Unverified
2Query-doc Small-E-Czech (Electra-small)P@1046.3—Unverified
3Siamese Small-E-Czech (Electra-small)P@1045.26—Unverified
#ModelMetricClaimedVerifiedStatus
1XLNetERR@2020.28—Unverified