SOTAVerified

Retrieval

A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.

Papers

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Showing 3576–3600 of 14297 papers

TitleStatusHype
Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized ContextsCode0
Entity Disambiguation via Fusion Entity Decoding—0
CLAPNQ: Cohesive Long-form Answers from Passages in Natural Questions for RAG systemsCode1
Dissecting Paraphrases: The Impact of Prompt Syntax and supplementary Information on Knowledge Retrieval from Pretrained Language Models—0
A Novel Audio Representation for Music Genre Identification in MIR—0
Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey—0
Towards an In-Depth Comprehension of Case Relevance for Better Legal Retrieval—0
ARAGOG: Advanced RAG Output GradingCode2
BERT-Enhanced Retrieval Tool for Homework Plagiarism Detection System—0
Query Performance Prediction using Relevance Judgments Generated by Large Language ModelsCode1
On Train-Test Class Overlap and Detection for Image RetrievalCode0
ECtHR-PCR: A Dataset for Precedent Understanding and Prior Case Retrieval in the European Court of Human RightsCode0
CuSINeS: Curriculum-driven Structure Induced Negative Sampling for Statutory Article Retrieval—0
RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation—0
Query-driven Relevant Paragraph Extraction from Legal Judgments—0
Generative Retrieval as Multi-Vector Dense RetrievalCode1
On the Estimation of Image-matching Uncertainty in Visual Place Recognition—0
Observations on Building RAG Systems for Technical Documents—0
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)Code2
M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language ModelsCode3
LAKE-RED: Camouflaged Images Generation by Latent Background Knowledge Retrieval-Augmented DiffusionCode2
Aligning Large Language Models with Recommendation Knowledge—0
Do Vision-Language Models Understand Compound Nouns?Code0
Multi-hop Question Answering under Temporal Knowledge Editing—0
Planning and Editing What You Retrieve for Enhanced Tool LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second183.53—Unverified
2ElasticsearchQueries per second21.8—Unverified
3BM25-PTQueries per second6.49—Unverified
4Rank-BM25Queries per second1.18—Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second20.88—Unverified
2ElasticsearchQueries per second7.11—Unverified
3Rank-BM25Queries per second0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second41.85—Unverified
2ElasticsearchQueries per second12.16—Unverified
3Rank-BM25Queries per second0.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FLMRRecall@589.32—Unverified
2RA-VQARecall@582.84—Unverified
#ModelMetricClaimedVerifiedStatus
1PreFLMRRecall@562.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP-KIStext-to-video Mean Rank30—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP4OutfitRecall@57.59—Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1—Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1—Unverified
#ModelMetricClaimedVerifiedStatus
1COLTCOMP@84.55—Unverified
#ModelMetricClaimedVerifiedStatus
1hello0L1,121,222—Unverified