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 3826–3850 of 14297 papers

TitleStatusHype
Digging Into Self-Supervised Learning of Feature Descriptors—0
Data Augmentation for Text-based Person Retrieval Using Large Language Models—0
Analysis of Robocode Robot Adaptive Confrontation Based on Zero-Sum Game—0
Dimensionality Detection and Integration of Multiple Data Sources via the GP-LVM—0
Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds—0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Dimension Projection among Languages based on Pseudo-relevant Documents for Query Translation—0
A Dataset for Sentence Retrieval for Open-Ended Dialogues—0
Billion-scale Similarity Search Using a Hybrid Indexing Approach with Advanced Filtering—0
DINER: Disorder-Invariant Implicit Neural Representation—0
DINOBot: Robot Manipulation via Retrieval and Alignment with Vision Foundation Models—0
DioR: Adaptive Cognitive Detection and Contextual Retrieval Optimization for Dynamic Retrieval-Augmented Generation—0
DIRA: Dialectal Arabic Information Retrieval Assistant—0
Efficient Retrieval of Logos Using Rough Set Reducts—0
Data Augmentation for Biomedical Factoid Question Answering—0
Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering—0
Automatic Separation of Compound Figures in Scientific Articles—0
Analysis of Plan-based Retrieval for Grounded Text Generation—0
Direction-Oriented Visual-semantic Embedding Model for Remote Sensing Image-text Retrieval—0
Direct optimization of F-measure for retrieval-based personal question answering—0
Accept the Modality Gap: An Exploration in the Hyperbolic Space—0
Computationally efficient reductions between some statistical models—0
DIR: Retrieval-Augmented Image Captioning with Comprehensive Understanding—0
Darwinian Model Upgrades: Model Evolving with Selective Compatibility—0
Automatic Recall of Software Lessons Learned for Software Project Managers—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