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 5426–5450 of 14297 papers

TitleStatusHype
Distribution Aligned Feature Clustering for Zero-Shot Sketch-Based Image Retrieval—0
Distributed Representations for Biological Sequence Analysis—0
An Intrinsic Framework of Information Retrieval Evaluation Measures—0
On Distributed Non-convex Optimization: Projected Subgradient Method For Weakly Convex Problems in Networks—0
Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes—0
Distributed Evolution of Deep Autoencoders—0
Distributed Evaluations: Ending Neural Point Metrics—0
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning—0
Advancing Retrieval-Augmented Generation for Persian: Development of Language Models, Comprehensive Benchmarks, and Best Practices for Optimization—0
A Compact Representation of Histopathology Images using Digital Stain Separation & Frequency-Based Encoded Local Projections—0
3218IR at SemEval-2020 Task 11: Conv1D and Word Embedding in Propaganda Span Identification at News Articles—0
Distributed Deep Learning for Persistent Monitoring of agricultural Fields—0
Distributed Data Vending on Blockchain—0
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions—0
Distortion-Aware Phase Retrieval Receiver for High-Order QAM Transmission with Carrierless Intensity-Only Measurements—0
Distinguishing artefacts: evaluating the saturation point of convolutional neural networks—0
Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models—0
An interactive engine for multilingual video browsing using semantic content—0
Distill-SynthKG: Distilling Knowledge Graph Synthesis Workflow for Improved Coverage and Efficiency—0
Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method—0
An Intent Taxonomy of Legal Case Retrieval—0
DistillPose: Lightweight Camera Localization Using Auxiliary Learning—0
Distilling Vision-Language Pretraining for Efficient Cross-Modal Retrieval—0
Bit-Scalable Deep Hashing with Regularized Similarity Learning for Image Retrieval and Person Re-identification—0
Distilling Vision-Language Models on Millions of Videos—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