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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 901–925 of 14297 papers

TitleStatusHype
STARD: A Chinese Statute Retrieval Dataset with Real Queries Issued by Non-professionalsCode1
CARE: a Benchmark Suite for the Classification and Retrieval of EnzymesCode1
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document AnalysisCode1
EAGER: Two-Stream Generative Recommender with Behavior-Semantic CollaborationCode1
Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge GraphsCode1
Insights into LLM Long-Context Failures: When Transformers Know but Don't TellCode1
Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted MetadataCode1
R^2AG: Incorporating Retrieval Information into Retrieval Augmented GenerationCode1
Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented GenerationCode1
Unified Active Retrieval for Retrieval Augmented GenerationCode1
Defending Against Social Engineering Attacks in the Age of LLMsCode1
TRACE the Evidence: Constructing Knowledge-Grounded Reasoning Chains for Retrieval-Augmented GenerationCode1
Few-Shot Recognition via Stage-Wise Retrieval-Augmented FinetuningCode1
R-Eval: A Unified Toolkit for Evaluating Domain Knowledge of Retrieval Augmented Large Language ModelsCode1
Language Modeling with Editable External KnowledgeCode1
DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed GraphsCode1
Neural Concept BinderCode1
Exploring the Spectrum of Visio-Linguistic Compositionality and RecognitionCode1
OpenObj: Open-Vocabulary Object-Level Neural Radiance Fields with Fine-Grained UnderstandingCode1
MINERS: Multilingual Language Models as Semantic RetrieversCode1
Bridging Language Gaps in Audio-Text RetrievalCode1
DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented GenerationCode1
On The Importance of Reasoning for Context Retrieval in Repository-Level Code EditingCode1
Document-level Claim Extraction and Decontextualisation for Fact-CheckingCode1
Interactive Text-to-Image Retrieval with Large Language Models: A Plug-and-Play ApproachCode1
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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