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 1901–1925 of 14297 papers

TitleStatusHype
CORAG: A Cost-Constrained Retrieval Optimization System for Retrieval-Augmented Generation—0
Towards Multi-Source Retrieval-Augmented Generation via Synergizing Reasoning and Preference-Driven Retrieval—0
Unified Generative and Discriminative Training for Multi-modal Large Language Models—0
MIRFLEX: Music Information Retrieval Feature Library for ExtractionCode1
Retrieval-enriched zero-shot image classification in low-resource domains—0
E2E-AFG: An End-to-End Model with Adaptive Filtering for Retrieval-Augmented Generation—0
Birdie: Advancing State Space Models with Reward-Driven Objectives and CurriculaCode1
JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking—0
MoTaDual: Modality-Task Dual Alignment for Enhanced Zero-shot Composed Image Retrieval—0
Beyond Content Relevance: Evaluating Instruction Following in Retrieval ModelsCode0
Towards Cross-Modal Text-Molecule Retrieval with Better Modality AlignmentCode0
Responsible Retrieval Augmented Generation for Climate Decision Making from Documents—0
TabM: Advancing Tabular Deep Learning with Parameter-Efficient EnsemblingCode4
Leveraging Large Language Models for Medical Information Extraction and Query Generation—0
LEAF: Learning and Evaluation Augmented by Fact-Checking to Improve Factualness in Large Language Models—0
Nearest Neighbor Normalization Improves Multimodal RetrievalCode1
RAGraph: A General Retrieval-Augmented Graph Learning FrameworkCode1
Multilingual Vision-Language Pre-training for the Remote Sensing DomainCode0
Mind the Gap: A Generalized Approach for Cross-Modal Embedding Alignment—0
Emotional RAG: Enhancing Role-Playing Agents through Emotional RetrievalCode1
HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models—0
SciPIP: An LLM-based Scientific Paper Idea ProposerCode2
Retrieval-Augmented Generation with Estimation of Source Reliability—0
Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval—0
Long^2RAG: Evaluating Long-Context & Long-Form Retrieval-Augmented Generation with Key Point Recall—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