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 1–50 of 168 papers

TitleStatusHype
Precise Zero-Shot Pointwise Ranking with LLMs through Post-Aggregated Global Context InformationCode0
Bridge the Gap between Past and Future: Siamese Model Optimization for Context-Aware Document Ranking—0
Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering—0
A Unified Retrieval Framework with Document Ranking and EDU Filtering for Multi-document Summarization—0
How do Large Language Models Understand Relevance? A Mechanistic Interpretability PerspectiveCode0
Beyond Reproducibility: Advancing Zero-shot LLM Reranking Efficiency with Setwise Insertion—0
Distillation and Refinement of Reasoning in Small Language Models for Document Re-rankingCode1
Graph-Based Re-ranking: Emerging Techniques, Limitations, and Opportunities—0
On Synthetic Data Strategies for Domain-Specific Generative Retrieval—0
White Hat Search Engine Optimization using Large Language Models—0
Beyond Questions: Leveraging ColBERT for Keyphrase SearchCode0
KeyB2: Selecting Key Blocks is Also Important for Long Document Ranking with Large Language Models—0
Multi-Field Adaptive Retrieval—0
DyVo: Dynamic Vocabularies for Learned Sparse Retrieval with EntitiesCode0
Efficient Document Ranking with Learnable Late Interactions—0
Weighted KL-Divergence for Document Ranking Model Refinement—0
RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented GenerationCode0
On the Evaluation of Machine-Generated Reports—0
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document RetrievalCode2
The Surprising Effectiveness of Rankers Trained on Expanded Queries—0
High Recall, Small Data: The Challenges of Within-System Evaluation in a Live Legal Search System—0
RankMamba: Benchmarking Mamba's Document Ranking Performance in the Era of TransformersCode1
Measuring Bias in a Ranked List using Term-based Representations—0
Query Augmentation by Decoding Semantics from Brain SignalsCode0
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMsCode0
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