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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 126–150 of 14297 papers

TitleStatusHype
Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language ModelsCode3
CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language ModelsCode3
Corrective Retrieval Augmented GenerationCode3
OpenResearcher: Unleashing AI for Accelerated Scientific ResearchCode3
MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop QueriesCode3
Multi-Head RAG: Solving Multi-Aspect Problems with LLMsCode3
ONE-PEACE: Exploring One General Representation Model Toward Unlimited ModalitiesCode3
Parametric Retrieval Augmented GenerationCode3
MoC: Mixtures of Text Chunking Learners for Retrieval-Augmented Generation SystemCode3
AlphaFin: Benchmarking Financial Analysis with Retrieval-Augmented Stock-Chain FrameworkCode3
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language ModelsCode3
MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare CopilotCode3
MegaPairs: Massive Data Synthesis For Universal Multimodal RetrievalCode3
MDocAgent: A Multi-Modal Multi-Agent Framework for Document UnderstandingCode3
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click LabelsCode3
PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational PathsCode3
REPLUG: Retrieval-Augmented Black-Box Language ModelsCode3
Ai2 Scholar QA: Organized Literature Synthesis with AttributionCode3
Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding ModelsCode3
LRP4RAG: Detecting Hallucinations in Retrieval-Augmented Generation via Layer-wise Relevance PropagationCode3
A GPU-specialized Inference Parameter Server for Large-Scale Deep Recommendation ModelsCode3
CHESS: Contextual Harnessing for Efficient SQL SynthesisCode3
Large Language Model based Long-tail Query Rewriting in Taobao SearchCode3
M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language ModelsCode3
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning TasksCode3
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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