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 8476–8500 of 14297 papers

TitleStatusHype
Hierarchical Memory Matching Network for Video Object SegmentationCode1
GradML: A Gradient-based Loss for Deep Metric Learning—0
Cross-Modal Coherence for Text-to-Image RetrievalCode0
Predicting Efficiency/Effectiveness Trade-offs for Dense vs. Sparse Retrieval Strategy Selection—0
Context-aware Tree-based Deep Model for Recommender Systems—0
Generating Compositional Color Representations from Text—0
RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsing—0
When expertise gone missing: Uncovering the loss of prolific contributors in Wikipedia—0
Learning Kernel-Smoothed Machine Translation with Retrieved ExamplesCode1
Audio Interval Retrieval using Convolutional Neural Networks—0
Homography augumented momentum constrastive learning for SAR image retrieval—0
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models—0
CONQUER: Contextual Query-aware Ranking for Video Corpus Moment RetrievalCode1
SPLADE v2: Sparse Lexical and Expansion Model for Information RetrievalCode1
Reliable Linearized Phase Retrieval for Near-Field Antenna Measurements with Truncated Measurement Surfaces—0
BERT Has Uncommon Sense: Similarity Ranking for Word Sense BERTologyCode0
Viewpoint Invariant Dense Matching for Visual GeolocalizationCode1
Sharp global convergence guarantees for iterative nonconvex optimization: A Gaussian process perspectiveCode0
Knowledge-Enhanced Evidence Retrieval for Counterargument GenerationCode0
Multilingual Molecular Representation Learning via Contrastive Pre-training—0
Backdoor Attack on Hash-based Image Retrieval via Clean-label Data PoisoningCode1
LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place RecognitionCode1
Towards Handling Unconstrained User Preferences in Dialogue—0
Slot Filling for Biomedical Information ExtractionCode0
Simple Entity-Centric Questions Challenge Dense RetrieversCode1
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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