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 5276–5300 of 14297 papers

TitleStatusHype
A Novel Audio Representation for Music Genre Identification in MIR—0
Adversarially Trained Deep Neural Semantic Hashing Scheme for Subjective Search in Fashion Inventory—0
Domain-matched Pre-training Tasks for Dense Retrieval—0
Leveraging Medical Foundation Model Features in Graph Neural Network-Based Retrieval of Breast Histopathology Images—0
Domain-invariant feature learning in brain MR imaging for content-based image retrieval—0
Domain Generalization with MixStyle—0
Break it Down for Me: A Study in Automated Lyric Annotation—0
A Novel Architecture For Question Classification Based Indexing Scheme For Efficient Question Answering—0
Domain Disentangled Generative Adversarial Network for Zero-Shot Sketch-Based 3D Shape Retrieval—0
Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs—0
Domain-Constrained Advertising Keyword Generation—0
Breaking the Lens of the Telescope: Online Relevance Estimation over Large Retrieval Sets—0
A Novel Approach to Eliminating Hallucinations in Large Language Model-Assisted Causal Discovery—0
Adversarial Learning of Hard Positives for Place Recognition—0
A Comparative Study of Text Retrieval Models on DaReCzech—0
Domain Adaptation of Multilingual Semantic Search - Literature Review—0
Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval—0
Domain Adaptation for Enterprise Email Search—0
BreakingNews: Article Annotation by Image and Text Processing—0
A Novel Approach to Develop a New Hybrid Technique for Trademark Image Retrieval—0
Domain Adaptation for Dense Retrieval through Self-Supervision by Pseudo-Relevance Labeling—0
Domain Adaptation for Dense Retrieval and Conversational Dense Retrieval through Self-Supervision by Meticulous Pseudo-Relevance Labeling—0
Bridging the Language Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs—0
DOLPHIn - Dictionary Learning for Phase Retrieval—0
DOLPH: Diffusion Models for Phase Retrieval—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