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 8926–8950 of 14297 papers

TitleStatusHype
Fine-grained Prototypical Voting with Heterogeneous Mixup for Semi-supervised 2D-3D Cross-modal Retrieval—0
Comparative Analysis of Retrieval Systems in the Real World—0
Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document—0
A Knowledge storage and semantic space alignment Method for Multi-documents dialogue generation—0
A Bayesian Model of Diachronic Meaning Change—0
Comparative Analysis of Neural QA models on SQuAD—0
Fine-Grained Instance-Level Sketch-Based Video Retrieval—0
Comparative Analysis of Melodia and Time-Domain Adaptive Filtering based Model for Melody Extraction from Polyphonic Music—0
Fine-grained Image Retrieval via Dual-Vision Adaptation—0
Legal Question-Answering in the Indian Context: Efficacy, Challenges, and Potential of Modern AI Models—0
Automating construction contract review using knowledge graph-enhanced large language models—0
Fine-Grained Image Analysis with Deep Learning: A Survey—0
Fine-Grained Histopathological Image Analysis via Robust Segmentation and Large-Scale Retrieval—0
Compact Hash Codes for Efficient Visual Descriptors Retrieval in Large Scale Databases—0
Fine-grained Hallucination Detection and Editing for Language Models—0
Fine-Grained Guidance for Retrievers: Leveraging LLMs' Feedback in Retrieval-Augmented Generation—0
Compact Hash Code Learning with Binary Deep Neural Network—0
Assisting humans in complex comparisons: automated information comparison at scale—0
Fine-Grained Distillation for Long Document Retrieval—0
Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings—0
Fine-Grain Annotation of Cricket Videos—0
Compact Deep Aggregation for Set Retrieval—0
A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions—0
Active Learning for Finely-Categorized Image-Text Retrieval by Selecting Hard Negative Unpaired Samples—0
FineFilter: A Fine-grained Noise Filtering Mechanism for Retrieval-Augmented Large Language Models—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