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 2126–2150 of 14297 papers

TitleStatusHype
MedMobile: A mobile-sized language model with expert-level clinical capabilitiesCode0
GIVE: Structured Reasoning with Knowledge Graph Inspired Veracity Extrapolation—0
RePD: Defending Jailbreak Attack through a Retrieval-based Prompt Decomposition Process—0
DyVo: Dynamic Vocabularies for Learned Sparse Retrieval with EntitiesCode0
No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users—0
The language of sound search: Examining User Queries in Audio Search Engines—0
Smart Audit System Empowered by LLM—0
Music Genre Classification using Large Language ModelsCode0
AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models—0
Modeling Alzheimer's Disease: From Memory Loss to Plaque & Tangles Formation—0
MRAG-Bench: Vision-Centric Evaluation for Retrieval-Augmented Multimodal Models—0
TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked TextCode2
CLIP Multi-modal Hashing for Multimedia Retrieval—0
The Function-Representation Model of Computation—0
Efficiently Learning at Test-Time: Active Fine-Tuning of LLMsCode2
Context-Augmented Code Generation Using Programming Knowledge Graphs—0
PAR: Prompt-Aware Token Reduction Method for Efficient Large Multimodal Models—0
The Cognitive Capabilities of Generative AI: A Comparative Analysis with Human Benchmarks—0
Does Vec2Text Pose a New Corpus Poisoning Threat?Code0
Enhancing Legal Case Retrieval via Scaling High-quality Synthetic Query-Candidate PairsCode1
Performance Evaluation in Multimedia Retrieval—0
Exploiting Distribution Constraints for Scalable and Efficient Image Retrieval—0
An Overview of zbMATH Open Digital Library—0
Dissecting Fine-Tuning Unlearning in Large Language ModelsCode1
LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning—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