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 8951–8975 of 14297 papers

TitleStatusHype
Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences for Image-Text Retrieval—0
Negative Sampling for Contrastive Representation Learning: A Review—0
Encode the Unseen: Predictive Video Hashing for Scalable Mid-Stream Retrieval—0
Neighborhood Preserving Hashing for Scalable Video Retrieval—0
Encoding CNN Activations for Writer Recognition—0
Neighbour Consistency Guided Pseudo-Label Refinement for Unsupervised Person Re-Identification—0
Efficient Image Gallery Representations at Scale Through Multi-Task Learning—0
NELS-Never-Ending Learner of Sounds—0
Multi-level Temporal-channel Speaker Retrieval for Zero-shot Voice Conversion—0
A plug-in approach to maximising precision at the top and recall at the top—0
Nested Graph Words for Object Recognition—0
Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval—0
Nested Named Entity Recognition with Span-level Graphs—0
EndoFinder: Online Image Retrieval for Explainable Colorectal Polyp Diagnosis—0
Net 835-Gb/s/λ Carrier- and LO-Free 100-km Transmission Using Channel-Aware Phase Retrieval Reception—0
Efficient Image Captioning for Edge Devices—0
Network-Clustered Multi-Modal Bug Localization—0
NEUCORE: Neural Concept Reasoning for Composed Image Retrieval—0
Neural Approaches to Conversational Information Retrieval—0
End-to-End Bangla AI for Solving Math Olympiad Problem Benchmark: Leveraging Large Language Model Using Integrated Approach—0
Generative Retrieval with Large Language Models—0
Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning—0
Multi-Layer Ranking with Large Language Models for News Source Recommendation—0
Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database—0
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching—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