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 1326–1350 of 14297 papers

TitleStatusHype
Shape-Based Single Object Classification Using Ensemble Method Classifiers—0
CyberMentor: AI Powered Learning Tool Platform to Address Diverse Student Needs in Cybersecurity EducationCode0
To Retrieve or Not to Retrieve? Uncertainty Detection for Dynamic Retrieval Augmented Generation—0
MMDocIR: Benchmarking Multi-Modal Retrieval for Long Documents—0
Guiding Retrieval using LLM-based Listwise RankersCode0
Continuous Approach to Phase (Norm) Retrieval Frames—0
Knowledge Graph-based Retrieval-Augmented Generation for Schema MatchingCode1
Agentic Retrieval-Augmented Generation: A Survey on Agentic RAGCode5
Benchmarking Robustness of Contrastive Learning Models for Medical Image-Report Retrieval—0
GOTPR: General Outdoor Text-based Place Recognition Using Scene Graph Retrieval with OpenStreetMapCode1
Leveraging Large Language Models as Knowledge-Driven Agents for Reliable Retrosynthesis PlanningCode1
Unsupervised Query Routing for Retrieval Augmented Generation—0
ADAM-1: AI and Bioinformatics for Alzheimer's Detection and Microbiome-Clinical Data Integrations—0
ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process RewardingCode4
Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models—0
Zero-shot Video Moment Retrieval via Off-the-shelf Multimodal Large Language Models—0
Talk to Right Specialists: Routing and Planning in Multi-agent System for Question Answering—0
Multimodal semantic retrieval for product searchCode0
Large Language Models: New Opportunities for Access to Science—0
Research on the Online Update Method for Retrieval-Augmented Generation (RAG) Model with Incremental Learning—0
Enhancing Retrieval-Augmented Generation: A Study of Best PracticesCode2
Rethinking Knowledge in Distillation: An In-context Sample Retrieval Perspective—0
Parallel Key-Value Cache Fusion for Position Invariant RAG—0
WebWalker: Benchmarking LLMs in Web TraversalCode11
The Devil is in the Spurious Correlation: Boosting Moment Retrieval via Temporal Dynamic Learning—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