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 476–500 of 14297 papers

TitleStatusHype
Retrieval with Learned SimilaritiesCode2
Beyond Matryoshka: Revisiting Sparse Coding for Adaptive RepresentationCode2
AiSAQ: All-in-Storage ANNS with Product Quantization for DRAM-free Information RetrievalCode2
Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse RepresentationsCode2
All in One: Exploring Unified Video-Language Pre-trainingCode2
ECG-Chat: A Large ECG-Language Model for Cardiac Disease DiagnosisCode2
Retrieval-Augmented Generation-based Relation ExtractionCode2
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMsCode2
Egocentric Video-Language PretrainingCode2
Extended Mind TransformersCode2
Retrieval-Augmented Perception: High-Resolution Image Perception Meets Visual RAGCode2
VeCLIP: Improving CLIP Training via Visual-enriched CaptionsCode2
DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language ModelsCode2
Contour Context: Abstract Structural Distribution for 3D LiDAR Loop Detection and Metric Pose EstimationCode2
Do You Remember? Dense Video Captioning with Cross-Modal Memory RetrievalCode2
Contrastive Audio-Visual Masked AutoencoderCode2
RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question AnsweringCode2
Retrieving Semantics from the Deep: an RAG Solution for Gesture SynthesisCode2
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam GenerationCode2
Duoduo CLIP: Efficient 3D Understanding with Multi-View ImagesCode2
Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge EnhancementCode2
Revisit Anything: Visual Place Recognition via Image Segment RetrievalCode2
Revisiting Contrastive Methods for Unsupervised Learning of Visual RepresentationsCode2
Document Expansion by Query PredictionCode2
Benchmarking Retrieval-Augmented Generation in Multi-Modal ContextsCode2
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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