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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 276–300 of 14297 papers

TitleStatusHype
CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and RerankingCode2
AudioSetCaps: An Enriched Audio-Caption Dataset using Automated Generation Pipeline with Large Audio and Language ModelsCode2
Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question AnsweringCode2
Multi-Reranker: Maximizing performance of retrieval-augmented generation in the FinanceRAG challengeCode2
Disentangling Memory and Reasoning Ability in Large Language ModelsCode2
Retrieval Augmented Time Series ForecastingCode2
Lightning IR: Straightforward Fine-tuning and Inference of Transformer-based Language Models for Information RetrievalCode2
HourVideo: 1-Hour Video-Language UnderstandingCode2
RAGViz: Diagnose and Visualize Retrieval-Augmented GenerationCode2
INQUIRE: A Natural World Text-to-Image Retrieval BenchmarkCode2
CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation GenerationCode2
SciPIP: An LLM-based Scientific Paper Idea ProposerCode2
Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial ApplicationsCode2
Retrieval-Enhanced Mutation Mastery: Augmenting Zero-Shot Prediction of Protein Language ModelCode2
Semantic Editing Increment Benefits Zero-Shot Composed Image RetrievalCode2
Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented GenerationCode2
Vision Search Assistant: Empower Vision-Language Models as Multimodal Search EnginesCode2
Retrieval-Augmented Diffusion Models for Time Series ForecastingCode2
LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question AnsweringCode2
RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data RewardsCode2
CLaMP 2: Multimodal Music Information Retrieval Across 101 Languages Using Large Language ModelsCode2
RAP: Retrieval-Augmented Personalization for Multimodal Large Language ModelsCode2
Toward General Instruction-Following Alignment for Retrieval-Augmented GenerationCode2
Retriever-and-Memory: Towards Adaptive Note-Enhanced Retrieval-Augmented GenerationCode2
TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked TextCode2
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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