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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 101–150 of 14297 papers

TitleStatusHype
RETSim: Resilient and Efficient Text SimilarityCode4
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionCode4
Retrieval-Generation Synergy Augmented Large Language ModelsCode4
Prompt2Model: Generating Deployable Models from Natural Language InstructionsCode4
Resources for Brewing BEIR: Reproducible Reference Models and an Official LeaderboardCode4
AlignScore: Evaluating Factual Consistency with a Unified Alignment FunctionCode4
AnnoLLM: Making Large Language Models to Be Better Crowdsourced AnnotatorsCode4
ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain KnowledgeCode4
Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionCode4
SLIM: Sparsified Late Interaction for Multi-Vector Retrieval with Inverted IndexesCode4
One Embedder, Any Task: Instruction-Finetuned Text EmbeddingsCode4
Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text RetrieversCode4
PLAID: An Efficient Engine for Late Interaction RetrievalCode4
What Makes Good In-Context Examples for GPT-3?Code4
Retrieval-Augmented Generation for Knowledge-Intensive NLP TasksCode4
FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented GenerationCode3
Hierarchical Lexical Graph for Enhanced Multi-Hop RetrievalCode3
When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented GenerationCode3
Distilling LLM Agent into Small Models with Retrieval and Code ToolsCode3
Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language ModelsCode3
Ai2 Scholar QA: Organized Literature Synthesis with AttributionCode3
REAL: Benchmarking Autonomous Agents on Deterministic Simulations of Real WebsitesCode3
RAKG:Document-level Retrieval Augmented Knowledge Graph ConstructionCode3
Beyond Quacking: Deep Integration of Language Models and RAG into DuckDBCode3
HyperGraphRAG: Retrieval-Augmented Generation with Hypergraph-Structured Knowledge RepresentationCode3
Retrieval Augmented Generation and Understanding in Vision: A Survey and New OutlookCode3
MDocAgent: A Multi-Modal Multi-Agent Framework for Document UnderstandingCode3
MoC: Mixtures of Text Chunking Learners for Retrieval-Augmented Generation SystemCode3
SelaVPR++: Towards Seamless Adaptation of Foundation Models for Efficient Place RecognitionCode3
A Comprehensive Survey on Composed Image RetrievalCode3
PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational PathsCode3
Any Information Is Just Worth One Single Screenshot: Unifying Search With Visualized Information RetrievalCode3
Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented GenerationCode3
Temporal Working Memory: Query-Guided Segment Refinement for Enhanced Multimodal UnderstandingCode3
MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare CopilotCode3
GFM-RAG: Graph Foundation Model for Retrieval Augmented GenerationCode3
Parametric Retrieval Augmented GenerationCode3
Unfolding the Headline: Iterative Self-Questioning for News Retrieval and Timeline SummarizationCode3
MegaPairs: Massive Data Synthesis For Universal Multimodal RetrievalCode3
Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language ModelsCode3
Video-RAG: Visually-aligned Retrieval-Augmented Long Video ComprehensionCode3
HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG SystemsCode3
Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning AgentCode3
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language ModelsCode3
Language-based Audio Moment RetrievalCode3
Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented GenerationCode3
Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding ModelsCode3
LRP4RAG: Detecting Hallucinations in Retrieval-Augmented Generation via Layer-wise Relevance PropagationCode3
RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented GenerationCode3
Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token RecyclingCode3
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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