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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 6626–6650 of 14297 papers

TitleStatusHype
Image-Text Retrieval with Binary and Continuous Label Supervision—0
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks—0
Communication breakdown: On the low mutual intelligibility between human and neural captioningCode0
Learning and Retrieval from Prior Data for Skill-based Imitation Learning—0
General Image Descriptors for Open World Image Retrieval using ViT CLIPCode1
An efficient graph generative model for navigating ultra-large combinatorial synthesis librariesCode1
Image Semantic Relation Generation—0
VTC: Improving Video-Text Retrieval with User CommentsCode1
Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph ConstructionCode1
Incorporating Relevance Feedback for Information-Seeking Retrieval using Few-Shot Document Re-RankingCode1
Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image RetrievalCode1
Holographic single particle imaging for weakly scattering, heterogeneous nanoscale objectsCode0
Revision Transformers: Instructing Language Models to Change their ValuesCode0
Whole Page Unbiased Learning to Rank—0
MuGER^2: Multi-Granularity Evidence Retrieval and Reasoning for Hybrid Question AnsweringCode2
Making a MIRACL: Multilingual Information Retrieval Across a Continuum of LanguagesCode2
MedCLIP: Contrastive Learning from Unpaired Medical Images and TextCode2
CPS-MEBR: Click Feedback-Aware Web Page Summarization for Multi-Embedding-Based Retrieval—0
Guiding Data-Driven Design Ideation by Knowledge Distance—0
Entity-Focused Dense Passage Retrieval for Outside-Knowledge Visual Question Answering—0
Uncertainty in Extreme Multi-label Classification—0
Towards Proactive Information Retrieval in Noisy Text with Wikipedia Concepts—0
CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with DemonstrationsCode0
CAVE: Correcting Attribute Values in E-commerce ProfilesCode0
Evaluating Search System Explainability with Psychometrics and Crowdsourcing—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