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 8851–8875 of 14297 papers

TitleStatusHype
Multi-view Point Cloud Registration with Adaptive Convergence Threshold and its Application on 3D Model Retrieval—0
Multi-view polarimetric scattering cloud tomography and retrieval of droplet size—0
Multi-View Product Image Search Using Deep ConvNets Representations—0
Multi-view Reconstructive Preserving Embedding for Dimension Reduction—0
Multi-view Recurrent Neural Acoustic Word Embeddings—0
Multi-View Task-Driven Recognition in Visual Sensor Networks—0
Efficient k-NN Search in IoT Data: Overlap Optimization in Tree-Based Indexing Structures—0
Multi-word Term Embeddings Improve Lexical Product Retrieval—0
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text—0
MURAL: Multimodal, Multitask Representations Across Languages—0
MURAL: Multimodal, Multitask Retrieval Across Languages—0
MuRAR: A Simple and Effective Multimodal Retrieval and Answer Refinement Framework for Multimodal Question Answering—0
Multilingual Test Sets for Machine Translation of Search Queries for Cross-Lingual Information Retrieval in the Medical Domain—0
Can MusicGen Create Training Data for MIR Tasks?—0
A Pooling Approach to Modelling Spatial Relations for Image Retrieval and Annotation—0
Embedding based on function approximation for large scale image search—0
Noisy Correspondence Learning with Self-Reinforcing Errors Mitigation—0
Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Task—0
Museum Painting Retrieval—0
Musical Features for Automatic Music Transcription Evaluation—0
Musical Information Extraction from the Singing Voice—0
Musical Prosody-Driven Emotion Classification: Interpreting Vocalists Portrayal of Emotions Through Machine Learning—0
Multilingual Representation Distillation with Contrastive Learning—0
Multilingual Open QA on the MIA Shared Task—0
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation—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