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 6101–6125 of 14297 papers

TitleStatusHype
An Approach For Transforming of Relational Databases to OWL Ontology—0
Deep Cross-Modal Hashing with Hashing Functions and Unified Hash Codes Jointly Learning—0
Deep Cross-Modal Correlation Learning for Audio and Lyrics in Music Retrieval—0
An approach based on Combination of Features for automatic news retrieval—0
A Deep Autoencoder System for Differentiation of Cancer Types Based on DNA Methylation State—0
Accuracy of the Uzbek stop words detection: a case study on "School corpus"—0
Deep Convolutional Features for Image Based Retrieval and Scene Categorization—0
Deep convolutional embedding for digitized painting clustering—0
Massively Multilingual Lexical Specialization of Multilingual Transformers—0
Deep Contextualized Biomedical Abbreviation Expansion—0
An Application of Manifold Learning in Global Shape Descriptors—0
A Zero-Shot Framework for Sketch based Image Retrieval—0
An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models—0
A Zero Attention Model for Personalized Product Search—0
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification—0
AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval—0
An analysis of vision-language models for fabric retrieval—0
Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval—0
Deep Belief Nets for Topic Modeling—0
Deep Barcodes for Fast Retrieval of Histopathology Scans—0
An Analysis of Variations in the Effectiveness of Query Performance Prediction—0
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data—0
Deep Attributes from Context-Aware Regional Neural Codes—0
Deep Asymmetric Metric Learning via Rich Relationship Mining—0
A White Box Analysis of ColBERT—0
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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