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 9776–9800 of 14297 papers

TitleStatusHype
Learning Visual Features from Snapshots for Web Search—0
Learning Visual Hierarchies with Hyperbolic Embeddings—0
Learning Visually Grounded Sentence Representations—0
Learning Visual N-Grams from Web Data—0
Learning Visual-Semantic Embeddings for Reporting Abnormal Findings on Chest X-rays—0
Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA—0
Learning with Batch-wise Optimal Transport Loss for 3D Shape Recognition—0
Learning with Label Noise for Image Retrieval by Selecting Interactions—0
Learning with Multi-modal Gradient Attention for Explainable Composed Image Retrieval—0
Learning with Noisy Correspondence—0
Learning with Noisy Triplet Correspondence for Composed Image Retrieval—0
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity—0
Learning World Models for Interactive Video Generation—0
LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop—0
Learnt quasi-transitive similarity for retrieval from large collections of faces—0
Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language Models—0
Least square ellipsoid fitting using iterative orthogonal transformations—0
LeCoPCR: Legal Concept-guided Prior Case Retrieval for European Court of Human Rights cases—0
Lecture Notes on Neural Information Retrieval—0
Lecture Presentations Multimodal Dataset: Towards Understanding Multimodality in Educational Videos—0
Legal document retrieval across languages: topic hierarchies based on synsets—0
Legal Document Retrieval using Document Vector Embeddings and Deep Learning—0
Legal Element-oriented Modeling with Multi-view Contrastive Learning for Legal Case Retrieval—0
Legal Question Answering using Ranking SVM and Deep Convolutional Neural Network—0
LegalRAG: A Hybrid RAG System for Multilingual Legal Information 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