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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 2951–2975 of 14297 papers

TitleStatusHype
MLLM-Guided VLM Fine-Tuning with Joint Inference for Zero-Shot Composed Image Retrieval—0
Anveshana: A New Benchmark Dataset for Cross-Lingual Information Retrieval On English Queries and Sanskrit Documents—0
LLM Web Dynamics: Tracing Model Collapse in a Network of LLMs—0
Hypercube-RAG: Hypercube-Based Retrieval-Augmented Generation for In-domain Scientific Question-AnsweringCode0
DocMMIR: A Framework for Document Multi-modal Information RetrievalCode0
RankLLM: A Python Package for Reranking with LLMs—0
DeepResearchGym: A Free, Transparent, and Reproducible Evaluation Sandbox for Deep Research—0
Distill CLIP (DCLIP): Enhancing Image-Text Retrieval via Cross-Modal Transformer Distillation—0
Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic DataCode0
Retrieval-Augmented Generation for Service Discovery: Chunking Strategies and Benchmarking—0
Aligning Web Query Generation with Ranking Objectives via Direct Preference Optimization—0
Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval Augmented Generation Across Learning Style—0
Structuring the Unstructured: A Multi-Agent System for Extracting and Querying Financial KPIs and Guidance—0
Self-Critique Guided Iterative Reasoning for Multi-hop Question AnsweringCode0
Knowledge Retrieval in LLM Gaming: A Shift from Entity-Centric to Goal-Oriented Graphs—0
REGen: Multimodal Retrieval-Embedded Generation for Long-to-Short Video Editing—0
EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models—0
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation—0
Vision Meets Language: A RAG-Augmented YOLOv8 Framework for Coffee Disease Diagnosis and Farmer AssistanceCode0
Supervised and Unsupervised protocols for hetero-associative neural networks—0
Federated Retrieval-Augmented Generation: A Systematic Mapping Study—0
RoleRAG: Enhancing LLM Role-Playing via Graph Guided Retrieval—0
Retrieval Augmented Decision-Making: A Requirements-Driven, Multi-Criteria Framework for Structured Decision Support—0
BRIT: Bidirectional Retrieval over Unified Image-Text Graph—0
Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems—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