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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 2601–2625 of 14297 papers

TitleStatusHype
Adaptive Contrastive Decoding in Retrieval-Augmented Generation for Handling Noisy Contexts—0
Toward Automatic Relevance Judgment using Vision--Language Models for Image--Text Retrieval Evaluation—0
RAGEval: Scenario Specific RAG Evaluation Dataset Generation FrameworkCode3
BioRAG: A RAG-LLM Framework for Biological Question Reasoning—0
Multi-Aspect Reviewed-Item Retrieval via LLM Query Decomposition and Aspect Fusion—0
Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up QuestionsCode4
Alleviating Hallucination in Large Vision-Language Models with Active Retrieval Augmentation—0
DeliLaw: A Chinese Legal Counselling System Based on a Large Language ModelCode2
Simple but Efficient: A Multi-Scenario Nearline Retrieval Framework for Recommendation on Taobao—0
Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text RetrievalCode1
Neural Graph Matching for Video Retrieval in Large-Scale Video-driven E-commerce—0
KemenkeuGPT: Leveraging a Large Language Model on Indonesia's Government Financial Data and Regulations to Enhance Decision Making—0
Adaptive Retrieval-Augmented Generation for Conversational Systems—0
Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins—0
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval—0
MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected TrainingCode2
SAKR: Enhancing Retrieval-Augmented Generation via Streaming Algorithm and K-Means Clustering—0
Multi-Level Querying using A Knowledge Pyramid—0
GEGA: Graph Convolutional Networks and Evidence Retrieval Guided Attention for Enhanced Document-level Relation Extraction—0
JaColBERTv2.5: Optimising Multi-Vector Retrievers to Create State-of-the-Art Japanese Retrievers with Constrained Resources—0
Prompt2DeModel: Declarative Neuro-Symbolic Modeling with Natural Language—0
Industrial-Grade Smart Troubleshooting through Causal Technical Language Processing: a Proof of Concept—0
X-ray nano-holotomography reconstruction with simultaneous probe retrieval—0
Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval—0
Introducing a new hyper-parameter for RAG: Context Window Utilization—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