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 6576–6600 of 14297 papers

TitleStatusHype
Improved Topic modeling in Twitter through Community Pooling—0
Improved Text-Image Matching by Mitigating Visual Semantic Hubs—0
Information Compression, Intelligence, Computing, and Mathematics—0
Information Need in Metaverse Recordings - A Field Study—0
Information Ranking Using Optimum-Path Forest—0
Information Retrieval and Classification of Real-Time Multi-Source Hurricane Evacuation Notices—0
Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings—0
Improved Search in Hamming Space using Deep Multi-Index Hashing—0
Information Retrieval and Natural Language Processing (Recherche d'Information et Traitement Automatique des Langues Naturelles) [in French]—0
Improved Radar Localization on Lidar Maps Using Shared Embedding—0
Information Retrieval for Climate Impact—0
Information retrieval for label noise document ranking by bag sampling and group-wise loss—0
Cross-modal Image Retrieval with Deep Mutual Information Maximization—0
Improved Hamming Distance Search Using Variable Length Substrings—0
Information Retrieval in African Languages—0
Cross-Modal Hamming Hashing—0
Information Retrieval in Friction Stir Welding of Aluminum Alloys by using Natural Language Processing based Algorithms—0
Information Retrieval in long documents: Word clustering approach for improving Semantics—0
Information retrieval in single cell chromatin analysis using TF-IDF transformation methods—0
AutoComPose: Automatic Generation of Pose Transition Descriptions for Composed Pose Retrieval Using Multimodal LLMs—0
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community—0
A Multi-View Embedding Space for Modeling Internet Images, Tags, and their Semantics—0
Information retrieval: recent advances and beyond—0
Improve Dense Passage Retrieval with Entailment Tuning—0
Improved Deep Metric Learning with Multi-class N-pair Loss Objective—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