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 8701–8725 of 14297 papers

TitleStatusHype
Multimodal Learned Sparse Retrieval for Image Suggestion—0
Application of the Non-Hermitian Singular Spectrum Analysis to the exponential retrieval problem—0
Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gap—0
Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks—0
Efficient Machine Translation Domain Adaptation—0
Application of Topic Models to Judgments from Public Procurement Domain—0
Multimodal Information Retrieval for Open World with Edit Distance Weak Supervision—0
Multi-modal image retrieval with random walk on multi-layer graphs—0
Efficiently Enabling Block Semantics and Data Updates in DNA Storage—0
Can We Find the Code? An Empirical Study of Google Scholar's Code Retrieval—0
CANVASEMB: Learning Layout Representation with Large-scale Pre-training for Graphic Design—0
Multi-Modal Generative Embedding Model—0
Multimodal Gaussian Process Latent Variable Models With Harmonization—0
Multi-modal Fusion and Query Refinement Network for Video Moment Retrieval and Highlight Detection—0
A Comprehensive Analysis of Real-World Image Captioning and Scene Identification—0
Nearest neighbor search with compact codes: A decoder perspective—0
Multimodal Learning with Deep Boltzmann Machines—0
Efficient Match Pair Retrieval for Large-scale UAV Images via Graph Indexed Global Descriptor—0
NeCo@ALQAC 2023: Legal Domain Knowledge Acquisition for Low-Resource Languages through Data Enrichment—0
Neighborhood Preserving Hashing for Scalable Video Retrieval—0
Multimodal Misinformation Detection using Large Vision-Language Models—0
Neural Bregman Divergences for Distance Learning—0
Neural ranking models for document retrieval—0
Multimodal Multihop Source Retrieval for Web Question Answering—0
Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections—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