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 8726–8750 of 14297 papers

TitleStatusHype
NEWSKVQA: Knowledge-Aware News Video Question Answering—0
Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections—0
Multi-Modal Mutual Information Maximization: A Novel Approach for Unsupervised Deep Cross-Modal Hashing—0
Multi-Modal Fashion Product Retrieval—0
Efficient Long Sequential User Data Modeling for Click-Through Rate Prediction—0
Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights—0
Multimodal or Text? Retrieval or BERT? Benchmarking Classifiers for the Shared Task on Hateful Memes—0
Multimodal Pivots for Image Caption Translation—0
Application of NotebookLM, a Large Language Model with Retrieval-Augmented Generation, for Lung Cancer Staging—0
Multimodal Entity Tagging with Multimodal Knowledge Base—0
Multimodal Dialogue Response Generation—0
Multimodal RAG-driven Anomaly Detection and Classification in Laser Powder Bed Fusion using Large Language Models—0
Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval—0
Efficient Length-Generalizable Attention via Causal Retrieval for Long-Context Language Modeling—0
Multi-Modal Cross-Domain Alignment Network for Video Moment Retrieval—0
Multi-Modal Relational Graph for Cross-Modal Video Moment Retrieval—0
Multi-modal Relation Distillation for Unified 3D Representation Learning—0
Efficient Long Context Language Model Retrieval with Compression—0
Multimodal Representation Alignment for Cross-modal Information Retrieval—0
Multi-modal Representation Learning for Social Post Location Inference—0
Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging—0
Multimodal Prediction based on Graph Representations—0
Multi-Modal Retrieval Augmentation for Open-Ended and Knowledge-Intensive Video Question Answering—0
Can't Hide Behind the API: Stealing Black-Box Commercial Embedding Models—0
NELS-Never-Ending Learner of Sounds—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