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 9576–9600 of 14297 papers

TitleStatusHype
Composition by Conversation—0
Compound virtual screening by learning-to-rank with gradient boosting decision tree and enrichment-based cumulative gain—0
Comprehending Knowledge Graphs with Large Language Models for Recommender Systems—0
Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling—0
Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering—0
Comprehensive Feature-based Robust Video Fingerprinting Using Tensor Model—0
Comprehensive Review on Semantic Information Retrieval and Ontology Engineering—0
Comprehensive Study on Denoising of Medical Images Utilizing Neural Network Based Auto-Encoder—0
Compressible and Searchable: AI-native Multi-Modal Retrieval System with Learned Image Compression—0
Compressing Sentence Representation via Homomorphic Projective Distillation—0
Compressing Sentence Representation with maximum Coding Rate Reduction—0
Compression of Deep Learning Models for Text: A Survey—0
Compression of Deep Neural Networks for Image Instance Retrieval—0
Compressive Change Retrieval for Moving Object Detection—0
Compressive Phase Retrieval: Optimal Sample Complexity with Deep Generative Priors—0
Compressive Quantization for Fast Object Instance Search in Videos—0
Compressive Shift Retrieval—0
Computational Approaches for App-to-App Retrieval and Design Consistency Check—0
Computationally Bounded Retrieval—0
Computationally Efficient Labeling of Cancer Related Forum Posts by Non-Clinical Text Information Retrieval—0
Computing Lexical Contrast—0
Computing with Cognitive States—0
ComRAG: Retrieval-Augmented Generation with Dynamic Vector Stores for Real-time Community Question Answering in Industry—0
ConaCLIP: Exploring Distillation of Fully-Connected Knowledge Interaction Graph for Lightweight Text-Image Retrieval—0
Concentric network symmetry grasps authors' styles in word adjacency networks—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