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 3451–3475 of 14297 papers

TitleStatusHype
DataOps for Societal Intelligence: a Data Pipeline for Labor Market Skills Extraction and Matching—0
DeepFashion: Powering Robust Clothes Recognition and Retrieval With Rich Annotations—0
Bag of Attributes for Video Event Retrieval—0
Deep Features for CBIR with Scarce Data using Hebbian Learning—0
Data Mining of Causal Relations from Text: Analysing Maritime Accident Investigation Reports—0
Analyzing and Learning from User Interactions for Search Clarification—0
Deep Frequency Filtering for Domain Generalization—0
Deep Fusion of Multi-attentive Local and Global Features with Higher Efficiency for Image Retrieval—0
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion—0
Deep Gaussian Processes for geophysical parameter retrieval—0
Deep Graph Matching and Searching for Semantic Code Retrieval—0
Bag-of-Words Baselines for Semantic Code Search—0
Data Management Challenges for Internet-scale 3D Search Engines—0
Data level and decision level fusion of satellite multi-sensor AOD retrievals for improving PM2.5 estimations, a study on Tehran—0
Deep Hashing Learning for Visual and Semantic Retrieval of Remote Sensing Images—0
AutoMerge: A Framework for Map Assembling and Smoothing in City-scale Environments—0
DeepHashing using TripletLoss—0
Deep Hashing with Active Pairwise Supervision—0
An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences—0
Deep Hashing with Hash Center Update for Efficient Image Retrieval—0
Deep Hashing with Hash-Consistent Large Margin Proxy Embeddings—0
Deep Hashing With Minimal-Distance-Separated Hash Centers—0
Deep Hashing with Triplet Quantization Loss—0
Deep Heterogeneous Hashing for Face Video Retrieval—0
Phase-based Minimalist Parsing and complexity in non-local dependencies—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