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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 2376–2400 of 14297 papers

TitleStatusHype
Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding ModelsCode3
A Sample Efficient Alternating Minimization-based Algorithm For Robust Phase Retrieval—0
Training-free Zero-shot Composed Image Retrieval via Weighted Modality Fusion and SimilarityCode0
Retrieval Augmented Generation-Based Incident Resolution Recommendation System for IT Support—0
Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized Academic Assistance—0
Zero-Shot Whole Slide Image Retrieval in Histopathology Using Embeddings of Foundation Models—0
Introducing a Class-Aware Metric for Monocular Depth Estimation: An Automotive PerspectiveCode0
Learning vs Retrieval: The Role of In-Context Examples in Regression with LLMsCode0
Vietnamese Legal Information Retrieval in Question-Answering System—0
Zeroshot Listwise Learning to Rank Algorithm for Recommendation—0
HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps—0
MARAGS: A Multi-Adapter System for Multi-Task Retrieval Augmented Generation Question Answering—0
Diversify-verify-adapt: Efficient and Robust Retrieval-Augmented Ambiguous Question Answering—0
Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?Code1
Design and Evaluation of Camera-Centric Mobile Crowdsourcing Applications—0
No Detail Left Behind: Revisiting Self-Retrieval for Fine-Grained Image Captioning—0
GenDFIR: Advancing Cyber Incident Timeline Analysis Through Retrieval Augmented Generation and Large Language Models—0
Language Model Powered Digital Biology with BRADCode2
NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for RetrievalCode1
RouterRetriever: Routing over a Mixture of Expert Embedding ModelsCode1
You Only Use Reactive Attention Slice For Long Context RetrievalCode0
Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical StudyCode0
In Defense of RAG in the Era of Long-Context Language Models—0
Optimizing CLIP Models for Image Retrieval with Maintained Joint-Embedding AlignmentCode0
Smoothed Robust Phase Retrieval—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