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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 201–250 of 14297 papers

TitleStatusHype
Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding ModelsCode3
M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language ModelsCode3
InPars-v2: Large Language Models as Efficient Dataset Generators for Information RetrievalCode2
InPars: Data Augmentation for Information Retrieval using Large Language ModelsCode2
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement LearningCode2
InPars Toolkit: A Unified and Reproducible Synthetic Data Generation Pipeline for Neural Information RetrievalCode2
INQUIRE: A Natural World Text-to-Image Retrieval BenchmarkCode2
Benchmarking Large Language Models in Retrieval-Augmented GenerationCode2
BEBLID: Boosted efficient binary local image descriptorCode2
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval ModelsCode2
Huatuo-26M, a Large-scale Chinese Medical QA DatasetCode2
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed RetrievalCode2
Improving Diffusion Inverse Problem Solving with Decoupled Noise AnnealingCode2
InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized RationalesCode2
HM-RAG: Hierarchical Multi-Agent Multimodal Retrieval Augmented GenerationCode2
Hello Again! LLM-powered Personalized Agent for Long-term DialogueCode2
Hopfield Networks is All You NeedCode2
Backtracing: Retrieving the Cause of the QueryCode2
HourVideo: 1-Hour Video-Language UnderstandingCode2
All in One: Exploring Unified Video-Language Pre-trainingCode2
Autoregressive Search Engines: Generating Substrings as Document IdentifiersCode2
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoMLCode2
GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook RetrievalCode2
All You Need to Know About Training Image Retrieval ModelsCode2
Autonomous GIS: the next-generation AI-powered GISCode2
Global Features are All You Need for Image Retrieval and RerankingCode2
How do you know that? Teaching Generative Language Models to Reference Answers to Biomedical QuestionsCode2
Interactive Continual Learning: Fast and Slow ThinkingCode2
Generating Images with Multimodal Language ModelsCode2
All-In-One Metrical And Functional Structure Analysis With Neighborhood Attentions on Demixed AudioCode2
Generating Benchmarks for Factuality Evaluation of Language ModelsCode2
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam GenerationCode2
Generalized Contrastive Learning for Multi-Modal Retrieval and RankingCode2
GENIUS: A Generative Framework for Universal Multimodal SearchCode2
Grounding Language Models to Images for Multimodal Inputs and OutputsCode2
AiSAQ: All-in-Storage ANNS with Product Quantization for DRAM-free Information RetrievalCode2
VeCLIP: Improving CLIP Training via Visual-enriched CaptionsCode2
GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical InformationCode2
FollowIR: Evaluating and Teaching Information Retrieval Models to Follow InstructionsCode2
Flow-Guided Transformer for Video InpaintingCode2
FreshDiskANN: A Fast and Accurate Graph-Based ANN Index for Streaming Similarity SearchCode2
AIR-Bench: Automated Heterogeneous Information Retrieval BenchmarkCode2
Fine-grained Image Captioning with CLIP RewardCode2
Search and Refine During Think: Autonomous Retrieval-Augmented Reasoning of LLMsCode2
Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question AnsweringCode2
Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph CompletionCode2
Benchmarking Retrieval-Augmented Generation in Multi-Modal ContextsCode2
Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language ModelsCode2
In-Context Retrieval-Augmented Language ModelsCode2
AudioSetCaps: An Enriched Audio-Caption Dataset using Automated Generation Pipeline with Large Audio and Language ModelsCode2
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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