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 6826–6850 of 14297 papers

TitleStatusHype
"Is this an example image?" -- Predicting the Relative Abstractness Level of Image and Text—0
Cross-Lingual Training with Dense Retrieval for Document Retrieval—0
Image retrieval method based on CNN and dimension reduction—0
Cross-Lingual Training of Neural Models for Document Ranking—0
Image Retrieval from Contextual Descriptions—0
Image Retrieval for Structure-from-Motion via Graph Convolutional Network—0
Cross-Lingual Training of Dense Retrievers for Document Retrieval—0
A Multimodal Multi-Agent Framework for Radiology Report Generation—0
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders—0
Image Retrieval for Arguments Using Stance-Aware Query Expansion—0
Image Retrieval Based on LBP Pyramidal Multiresolution using Reversible Watermarking—0
Image Retrieval Based on Binary Signature ang S-kGraph—0
It's About Time: Incorporating Temporality in Retrieval Augmented Language Models—0
Image Retrieval based on Bag-of-Words model—0
Image retrieval approach based on local texture information derived from predefined patterns and spatial domain information—0
Image Retrieval and Pattern Spotting using Siamese Neural Network—0
Image Retrieval And Classification Using Local Feature Vectors—0
ITTC @ TREC 2021 Clinical Trials Track—0
I Want This Product but Different : Multimodal Retrieval with Synthetic Query Expansion—0
Towards Better Monolingual Japanese Retrievers with Multi-Vector Models—0
JaColBERTv2.5: Optimising Multi-Vector Retrievers to Create State-of-the-Art Japanese Retrievers with Constrained Resources—0
Crosslingual Retrieval Augmented In-context Learning for Bangla—0
Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories—0
Image Reconstruction from Bag-of-Visual-Words—0
ImageRAG: Dynamic Image Retrieval for Reference-Guided Image Generation—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