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 10401–10425 of 14297 papers

TitleStatusHype
Document Image Binarization in JPEG Compressed Domain using Dual Discriminator Generative Adversarial Networks—0
Document image classification, with a specific view on applications of patent images—0
Document Layout Analysis via Dynamic Residual Feature Fusion—0
Document Network Embedding: Coping for Missing Content and Missing Links—0
Document Network Projection in Pretrained Word Embedding Space—0
Document Retrieval and Claim Verification to Mitigate COVID-19 Misinformation—0
Document retrieval and question answering in medical documents. A large-scale corpus challenge.—0
Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments—0
Document Retrieval for Large Scale Content Analysis using Contextualized Dictionaries—0
Document Retrieval on Repetitive String Collections—0
Document Retrieval using Predication Similarity—0
Documents as multiple overlapping windows into grids of counts—0
Document Selection in a Distributed Search Engine Architecture—0
Document Translation vs. Query Translation for Cross-Lingual Information Retrieval in the Medical Domain—0
Document Visual Question Answering Challenge 2020—0
Do deep neural networks possess concept space grid cells?—0
Does RAG Really Perform Bad For Long-Context Processing?—0
Does your robot know? Enhancing children's information retrieval through spoken conversation with responsible robots—0
Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA—0
DOGR: Leveraging Document-Oriented Contrastive Learning in Generative Retrieval—0
Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers—0
DOLPH: Diffusion Models for Phase Retrieval—0
DOLPHIn - Dictionary Learning for Phase Retrieval—0
Domain Adaptation for Dense Retrieval and Conversational Dense Retrieval through Self-Supervision by Meticulous Pseudo-Relevance Labeling—0
Domain Adaptation for Dense Retrieval through Self-Supervision by Pseudo-Relevance Labeling—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