SOTAVerified

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 13501–13550 of 14297 papers

TitleStatusHype
Optimizing Query Generation for Enhanced Document Retrieval in RAG—0
Optimizing open-domain question answering with graph-based retrieval augmented generation—0
Unifying Generative and Dense Retrieval for Sequential Recommendation—0
Optimizing Multi-Stage Language Models for Effective Text Retrieval—0
Unifying Latent and Lexicon Representations for Effective Video-Text Retrieval—0
Unifying Multimodal Retrieval via Document Screenshot Embedding—0
Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition—0
Unifying Remote Sensing Image Retrieval and Classification with Robust Fine-tuning—0
Optimizing Multi-Hop Document Retrieval Through Intermediate Representations—0
Unifying Vision-Language Representation Space with Single-tower Transformer—0
UniGen: A Unified Generative Framework for Retrieval and Question Answering with Large Language Models—0
UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting—0
Optimizing Leaky Private Information Retrieval Codes to Achieve O( K) Leakage Ratio Exponent—0
UniIR: Training and Benchmarking Universal Multimodal Information Retrievers—0
Optimizing Knowledge Integration in Retrieval-Augmented Generation with Self-Selection—0
UniMC: A Unified Framework for Long-Term Memory Conversation via Relevance Representation Learning—0
UNIMIB at TREC 2021 Clinical Trials Track—0
Uni-Mlip: Unified Self-supervision for Medical Vision Language Pre-training—0
UniMS-RAG: A Unified Multi-source Retrieval-Augmented Generation for Personalized Dialogue Systems—0
Optimizing example selection for retrieval-augmented machine translation with translation memories—0
Optimizing Domain-Specific Image Retrieval: A Benchmark of FAISS and Annoy with Fine-Tuned Features—0
Uniqueness of phase retrieval from offset linear canonical transform—0
Optimizing Contextual Speech Recognition Using Vector Quantization for Efficient Retrieval—0
Uni-Retrieval: A Multi-Style Retrieval Framework for STEM's Education—0
UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrieval—0
Uni-Retriever: Towards Learning The Unified Embedding Based Retriever in Bing Sponsored Search—0
UniRQR: A Unified Model for Retrieval Decision, Query, and Response Generation in Internet-Based Knowledge Dialogue Systems—0
UniRVQA: A Unified Framework for Retrieval-Augmented Vision Question Answering via Self-Reflective Joint Training—0
UnitedQA: A Hybrid Approach for Open Domain Question Answering—0
UNITER: Learning UNiversal Image-TExt Representations—0
Optimizing Compound Retrieval Systems—0
UniUD-FBK-UB-UniBZ Submission to the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge 2022—0
UniUD Submission to the EPIC-Kitchens-100 Multi-Instance Retrieval Challenge 2023—0
Universal Adversarial Head: Practical Protection against Video Data Leakage—0
Generating More Pertinent Captions by Leveraging Semantics and Style on Multi-Source Datasets—0
Optimizing Component Combination in a Multi-Indexing Paragraph Retrieval System—0
Optimizing affinity-based binary hashing using auxiliary coordinates—0
Universal Information Extraction with Meta-Pretrained Self-Retrieval—0
Optimize What You Evaluate With: A Simple Yet Effective Framework For Direct Optimization Of IR Metrics—0
Universal Model for Multi-Domain Medical Image Retrieval—0
Universal Model in Online Customer Service—0
Optimized Quran Passage Retrieval Using an Expanded QA Dataset and Fine-Tuned Language Models—0
Universal Multimodal Representation for Language Understanding—0
Word Searching in Scene Image and Video Frame in Multi-Script Scenario using Dynamic Shape Coding—0
Universal Perturbation Attack Against Image Retrieval—0
Optimized Feedforward Neural Network Training for Efficient Brillouin Frequency Shift Retrieval in Fiber—0
Universal representation by Boltzmann machines with Regularised Axons—0
Universal Sentence Representation Learning with Conditional Masked Language Model—0
Universal Sentence Representations Learning with Conditional Masked Language Model—0
Universal Sketch Perceptual Grouping—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