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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 1926–1950 of 14297 papers

TitleStatusHype
Eliciting Critical Reasoning in Retrieval-Augmented Language Models via Contrastive Explanations—0
Emotional RAG: Enhancing Role-Playing Agents through Emotional RetrievalCode1
Retrieval-Augmented Approach for Unsupervised Anomalous Sound Detection and Captioning without Model Training—0
PerSRV: Personalized Sticker Retrieval with Vision-Language ModelCode0
RealCQA-V2 : Visual Premise Proving A Manual COT Dataset for Charts—0
Application of Audio Fingerprinting Techniques for Real-Time Scalable Speech Retrieval and Speech Clusterization—0
Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial ApplicationsCode2
Not All Languages are Equal: Insights into Multilingual Retrieval-Augmented GenerationCode0
Understanding Synthetic Context Extension via Retrieval Heads—0
ContextIQ: A Multimodal Expert-Based Video Retrieval System for Contextual AdvertisingCode0
Semantic Editing Increment Benefits Zero-Shot Composed Image RetrievalCode2
Calibrated Decision-Making through LLM-Assisted Retrieval—0
SandboxAQ's submission to MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrieval—0
Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise LevelsCode0
Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert KnowledgeCode1
AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation PipelineCode7
Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented GenerationCode2
PlanRAG: Planning-guided Retrieval Augmented Generation—0
LLMs are Biased Evaluators But Not Biased for Retrieval Augmented GenerationCode0
Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language ModelCode2
Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback—0
FACT: Examining the Effectiveness of Iterative Context Rewriting for Multi-fact Retrieval—0
Vision Search Assistant: Empower Vision-Language Models as Multimodal Search EnginesCode2
What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration—0
WindTunnel -- A Framework for Community Aware Sampling of Large Corpora—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