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 7526–7550 of 14297 papers

TitleStatusHype
Learning to Exploit Different Translation Resources for Cross Language Information Retrieval—0
A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition—0
How Can Context Help? Exploring Joint Retrieval of Passage and Personalized Context—0
CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrieval—0
How are journals cited? characterizing journal citations by type of citation—0
Cost-sensitive detection with variational autoencoders for environmental acoustic sensing—0
Learning to Hash-tag Videos with Tag2Vec—0
Learning to Hash with Binary Reconstructive Embeddings—0
Learning to Hash with Graph Neural Networks for Recommender Systems—0
Learning to hash with semantic similarity metrics and empirical KL divergence—0
Learning to Interpret and Describe Abstract Scenes—0
AttWalk: Attentive Cross-Walks for Deep Mesh Analysis—0
HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification—0
Learning to Learn in a Semi-Supervised Fashion—0
Learning to Link—0
Attributes Grouping and Mining Hashing for Fine-Grained Image Retrieval—0
A method to Suppress Facial Expression in Posed and Spontaneous Videos—0
Adaptive Hashing for Fast Similarity Search—0
Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval—0
Hotel Recognition via Latent Image Embedding—0
HORUS: Multimodal Large Language Models Framework for Video Retrieval at VBS 2025—0
Horizon Scans can be accelerated using novel information retrieval and artificial intelligence tools—0
CosmoCLIP: Generalizing Large Vision-Language Models for Astronomical Imaging—0
HopRetriever: Retrieve Hops over Wikipedia to Answer Complex Questions—0
HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation—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