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 8126–8150 of 14297 papers

TitleStatusHype
MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders are Better Dense Retrievers—0
GVCNN: Group-View Convolutional Neural Networks for 3D Shape Recognition—0
A Machine Learning Framework for Authorship Identification From Texts—0
GUMsley: Evaluating Entity Salience in Summarization for 12 English Genres—0
Conversation AI Dialog for Medicare powered by Finetuning and Retrieval Augmented Generation—0
Guiding Neural Machine Translation with Retrieved Translation Pieces—0
Guiding Interaction Behaviors for Multi-modal Grounded Language Learning—0
Guiding Data-Driven Design Ideation by Knowledge Distance—0
Guided Unsupervised Learning by Subaperture Decomposition for Ocean SAR Image Retrieval—0
Convergence of Learning Dynamics in Information Retrieval Games—0
Matching Tweets With Applicable Fact-Checks Across Languages—0
Match Your Words! A Study of Lexical Matching in Neural Information Retrieval—0
A Topological Method for Comparing Document Semantics—0
A Machine Learning Data Fusion Model for Soil Moisture Retrieval—0
Guided Transformer: Leveraging Multiple External Sources for Representation Learning in Conversational Search—0
Conv-CoA: Improving Open-domain Question Answering in Large Language Models via Conversational Chain-of-Action—0
MATERIALizing Cross-Language Information Retrieval: A Snapshot—0
GS-Pose: Generalizable Segmentation-based 6D Object Pose Estimation with 3D Gaussian Splatting—0
MathAlign: Linking Formula Identifiers to their Contextual Natural Language Descriptions—0
MathBERT: A Pre-Trained Model for Mathematical Formula Understanding—0
Mathematical Information Retrieval based on Type Embeddings and Query Expansion—0
Control Token with Dense Passage Retrieval—0
Role Taxonomy of Units in Deep Neural Networks—0
GS-CLIP: Gaussian Splatting for Contrastive Language-Image-3D Pretraining from Real-World Data—0
Control Search Rankings, Control the World: What is a Good Search Engine?—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