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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 2926–2950 of 14297 papers

TitleStatusHype
Beyond True or False: Retrieval-Augmented Hierarchical Analysis of Nuanced ClaimsCode0
2D Matryoshka Training for Information RetrievalCode0
LEGAL-UQA: A Low-Resource Urdu-English Dataset for Legal Question AnsweringCode0
Learn to Understand Negation in Video RetrievalCode0
Learning Without LossCode0
Extractive Explanations for Interpretable Text RankingCode0
A DQN-based Approach to Finding Precise Evidences for Fact VerificationCode0
Beyond Short Snippets: Deep Networks for Video ClassificationCode0
Beyond Seen Data: Improving KBQA Generalization Through Schema-Guided Logical Form GenerationCode0
A Closer Look at Reference Learning for Fourier Phase RetrievalCode0
Learning with Average Precision: Training Image Retrieval with a Listwise LossCode0
An Evaluation Framework for Attributed Information Retrieval using Large Language ModelsCode0
LeCaRDv2: A Large-Scale Chinese Legal Case Retrieval DatasetCode0
Learning Unseen Modality InteractionCode0
Learning Two-Branch Neural Networks for Image-Text Matching TasksCode0
Beyond Relevance: Evaluate and Improve Retrievers on Perspective AwarenessCode0
Learning to Weight for Text ClassificationCode0
Learning Visual Actions Using Multiple Verb-Only LabelsCode0
Beyond Questions: Leveraging ColBERT for Keyphrase SearchCode0
Learning to Speak and Act in a Fantasy Text Adventure GameCode0
Beyond Product Quantization: Deep Progressive Quantization for Image RetrievalCode0
Learning to Search in Long Documents Using Document StructureCode0
Learning Visual Importance for Graphic Designs and Data VisualizationsCode0
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)Code0
Beyond MeSH: Fine-Grained Semantic Indexing of Biomedical Literature based on Weak SupervisionCode0
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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