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 10851–10875 of 14297 papers

TitleStatusHype
Precision-Recall Curves Using Information Divergence Frontiers—0
Evaluating Information Retrieval Systems for Kids—0
Evaluating Knowledge Graph Based Retrieval Augmented Generation Methods under Knowledge Incompleteness—0
DiffuSyn Bench: Evaluating Vision-Language Models on Real-World Complexities with Diffusion-Generated Synthetic Benchmarks—0
Evaluating Lexical Similarity to build Sentiment Similarity—0
Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset—0
Evaluating Local Geometric Feature Representations for 3D Rigid Data Matching—0
Evaluating Long Range Dependency Handling in Code Generation Models using Multi-Step Key Retrieval—0
Evaluating Machine Translation in Cross-lingual E-Commerce Search—0
Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions—0
Evaluating Quality of Answers for Retrieval-Augmented Generation: A Strong LLM Is All You Need—0
Evaluating Recipes Generated from Functional Object-Oriented Network—0
Evaluating Recognizing Question Entailment Methods for a Portuguese Community Question-Answering System about Diabetes Mellitus—0
Evaluating Research Dataset Recommendations in a Living Lab—0
Evaluating Retrieval Augmented Generative Models for Document Queries in Transportation Safety—0
Evaluating Retrieval for Multi-domain Scientific Publications—0
Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions—0
Evaluating Search System Explainability with Psychometrics and Crowdsourcing—0
Evaluating Self-Generated Documents for Enhancing Retrieval-Augmented Generation with Large Language Models—0
Evaluating Sentence-Level Relevance Feedback for High-Recall Information Retrieval—0
Evaluating Stochastic Rankings with Expected Exposure—0
Evaluating Temporal Persistence Using Replicability Measures—0
Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning—0
Evaluating the Effect of Retrieval Augmentation on Social Biases—0
Evaluating the reliability of acoustic speech embeddings—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