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 3226–3250 of 14297 papers

TitleStatusHype
Barwise Music Structure Analysis with the Correlation Block-Matching Segmentation Algorithm—0
An Effective Automatic Image Annotation Model Via Attention Model and Data Equilibrium—0
Barking Up The Syntactic Tree: Enhancing VLM Training with Syntactic Losses—0
Barcodes for Medical Image Retrieval Using Autoencoded Radon Transform—0
ANEC: An Amharic Named Entity Corpus and Transformer Based Recognizer—0
Accurate and Fast Retrieval for Complex Non-metric Data via Neighborhood Graphs—0
Golden-Retriever: High-Fidelity Agentic Retrieval Augmented Generation for Industrial Knowledge Base—0
Aligning Proteins and Language: A Foundation Model for Protein Retrieval—0
Differential EEG Characteristics during Working Memory Encoding and Re-encoding—0
Bandlimited signal reconstruction from leaky integrate-and-fire encoding using POCS—0
BanditRank: Learning to Rank Using Contextual Bandits—0
A deep learning approach to clustering visual arts—0
Differential Geometric Retrieval of Deep Features—0
PrivateMail: Supervised Manifold Learning of Deep Features With Differential Privacy for Image Retrieval—0
Differentiating Phrase Structure Parsing and Memory Retrieval in the Brain—0
Bandit Phase Retrieval—0
Anchor Graph Structure Fusion Hashing for Cross-Modal Similarity Search—0
Anchor-aware Deep Metric Learning for Audio-visual Retrieval—0
Balancing Sparsity and Rank Constraints in Quadratic Basis Pursuit—0
A Deep Learning Approach for Selective Relevance Feedback—0
Differentiable Top-k Operator with Optimal Transport—0
Balancing Reinforcement Learning Training Experiences in Interactive Information Retrieval—0
An Axiomatic Approach to Regularizing Neural Ranking Models—0
Accurate and Fast Pixel Retrieval with Spatial and Uncertainty Aware Hypergraph Diffusion—0
Balancing Content Size in RAG-Text2SQL System—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