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 1651–1675 of 14297 papers

TitleStatusHype
Binary Embedding-based Retrieval at TencentCode1
Learning Kernel-Smoothed Machine Translation with Retrieved ExamplesCode1
Automatic Spatially-aware Fashion Concept DiscoveryCode1
Learning More Effective Representations for Dense Retrieval through Deliberate Thinking Before SearchCode1
AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image MatchingCode1
Learning Passage Impacts for Inverted IndexesCode1
Learning Relation Alignment for Calibrated Cross-modal RetrievalCode1
Learning Semantic Relationship Among Instances for Image-Text MatchingCode1
Learning SO(3) Equivariant Representations with Spherical CNNsCode1
Learning Sparse Analytic Filters for Piano TranscriptionCode1
Learning Super-Features for Image RetrievalCode1
Learning the Best Pooling Strategy for Visual Semantic EmbeddingCode1
Cross-Modal Adapter for Text-Video RetrievalCode1
BioImage.IO Chatbot: A Community-Driven AI Assistant for Integrative Computational BioimagingCode1
Learning To Generate Piano Music With Sustain PedalsCode1
Learning Token-based Representation for Image RetrievalCode1
Cross-document Event Coreference Search: Task, Dataset and ModelingCode1
Semantic-Fused Multi-Granularity Cross-City Traffic PredictionCode1
Learning to Relate to Previous Turns in Conversational SearchCode1
Learning to Rematch Mismatched Pairs for Robust Cross-Modal RetrievalCode1
Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility StudyCode1
Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCOCode1
Learning to Tokenize for Generative RetrievalCode1
AutoPhaseNN: Unsupervised Physics-aware Deep Learning of 3D Nanoscale Bragg Coherent Diffraction ImagingCode1
CrIBo: Self-Supervised Learning via Cross-Image Object-Level BootstrappingCode1
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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