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 1801–1825 of 14297 papers

TitleStatusHype
Adopting RAG for LLM-Aided Future Vehicle Design—0
Harnessing multiple LLMs for Information Retrieval: A case study on Deep Learning methodologies in Biodiversity publicationsCode0
Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering—0
Information Need in Metaverse Recordings - A Field Study—0
A Transformer-Based Visual Piano Transcription Algorithm—0
Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data—0
MIRe: Enhancing Multimodal Queries Representation via Fusion-Free Modality Interaction for Multimodal RetrievalCode0
Building Trustworthy AI: Transparent AI Systems via Large Language Models, Ontologies, and Logical Reasoning (TranspNet)—0
Neural Corrective Machine Unranking—0
Retrieval Augmented Recipe Generation—0
Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle—0
Hopfield-Fenchel-Young Networks: A Unified Framework for Associative Memory RetrievalCode0
Saliency Map-based Image Retrieval using Invariant Krawtchouk MomentsCode0
Retrieval, Reasoning, Re-ranking: A Context-Enriched Framework for Knowledge Graph Completion—0
Retrieval of sun-induced plant fluorescence in the O_2-A absorption band from DESIS imagery—0
Retrieval Augmented Time Series ForecastingCode2
Improving Grapheme-to-Phoneme Conversion through In-Context Knowledge Retrieval with Large Language Models—0
Kernel-based retrieval models for hyperspectral image data optimized with Kernel Flows—0
ImageRAG: Enhancing Ultra High Resolution Remote Sensing Imagery Analysis with ImageRAGCode1
Unlocking Legal Knowledge with Multi-Layered Embedding-Based Retrieval—0
Likelihood as a Performance Gauge for Retrieval-Augmented GenerationCode0
Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models—0
Problem-Oriented Segmentation and Retrieval: Case Study on Tutoring ConversationsCode1
Firing Rate Models as Associative Memory: Excitatory-Inhibitory Balance for Robust Retrieval—0
Invar-RAG: Invariant LLM-aligned Retrieval for Better Generation—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