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

Showing 301350 of 14297 papers

TitleStatusHype
Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial ApplicationsCode2
HM-RAG: Hierarchical Multi-Agent Multimodal Retrieval Augmented GenerationCode2
Hello Again! LLM-powered Personalized Agent for Long-term DialogueCode2
Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based RetrieversCode2
Beyond Matryoshka: Revisiting Sparse Coding for Adaptive RepresentationCode2
Huatuo-26M, a Large-scale Chinese Medical QA DatasetCode2
InPars-v2: Large Language Models as Efficient Dataset Generators for Information RetrievalCode2
BEVPlace: Learning LiDAR-based Place Recognition using Bird's Eye View ImagesCode2
Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge EnhancementCode2
GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook RetrievalCode2
All You Need to Know About Training Image Retrieval ModelsCode2
GiantMIDI-Piano: A large-scale MIDI dataset for classical piano musicCode2
Global Features are All You Need for Image Retrieval and RerankingCode2
Generating Images with Multimodal Language ModelsCode2
Generating Benchmarks for Factuality Evaluation of Language ModelsCode2
GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical InformationCode2
ActiveRAG: Autonomously Knowledge Assimilation and Accommodation through Retrieval-Augmented AgentsCode2
An Autonomous GIS Agent Framework for Geospatial Data RetrievalCode2
Generalized Contrastive Learning for Multi-Modal Retrieval and RankingCode2
GENIUS: A Generative Framework for Universal Multimodal SearchCode2
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval ModelsCode2
VeCLIP: Improving CLIP Training via Visual-enriched CaptionsCode2
FollowIR: Evaluating and Teaching Information Retrieval Models to Follow InstructionsCode2
FreshDiskANN: A Fast and Accurate Graph-Based ANN Index for Streaming Similarity SearchCode2
BEBLID: Boosted efficient binary local image descriptorCode2
Benchmarking Retrieval-Augmented Generation in Multi-Modal ContextsCode2
Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question AnsweringCode2
Backtracing: Retrieving the Cause of the QueryCode2
FLAIR: VLM with Fine-grained Language-informed Image RepresentationsCode2
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed RetrievalCode2
AiSAQ: All-in-Storage ANNS with Product Quantization for DRAM-free Information RetrievalCode2
Benchmarking Large Language Models in Retrieval-Augmented GenerationCode2
Fine-grained Image Captioning with CLIP RewardCode2
FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation SystemsCode2
Atlas: Few-shot Learning with Retrieval Augmented Language ModelsCode2
Active Retrieval Augmented GenerationCode2
Autoregressive Search Engines: Generating Substrings as Document IdentifiersCode2
Flow-Guided Transformer for Video InpaintingCode2
Grounding Language Models to Images for Multimodal Inputs and OutputsCode2
INQUIRE: A Natural World Text-to-Image Retrieval BenchmarkCode2
All in One: Exploring Unified Video-Language Pre-trainingCode2
All-In-One Metrical And Functional Structure Analysis With Neighborhood Attentions on Demixed AudioCode2
Extended Mind TransformersCode2
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoMLCode2
GLAP: General contrastive audio-text pretraining across domains and languagesCode2
Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image RetrievalCode2
Autonomous GIS: the next-generation AI-powered GISCode2
Exploring the best way for UAV visual localization under Low-altitude Multi-view Observation Condition: a BenchmarkCode2
Evaluating RAG-Fusion with RAGElo: an Automated Elo-based FrameworkCode2
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam GenerationCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second183.53Unverified
2ElasticsearchQueries per second21.8Unverified
3BM25-PTQueries per second6.49Unverified
4Rank-BM25Queries per second1.18Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second20.88Unverified
2ElasticsearchQueries per second7.11Unverified
3Rank-BM25Queries per second0.04Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second41.85Unverified
2ElasticsearchQueries per second12.16Unverified
3Rank-BM25Queries per second0.1Unverified
#ModelMetricClaimedVerifiedStatus
1FLMRRecall@589.32Unverified
2RA-VQARecall@582.84Unverified
#ModelMetricClaimedVerifiedStatus
1PreFLMRRecall@562.1Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP-KIStext-to-video Mean Rank30Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP4OutfitRecall@57.59Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1Unverified
#ModelMetricClaimedVerifiedStatus
1COLTCOMP@84.55Unverified
#ModelMetricClaimedVerifiedStatus
1hello0L1,121,222Unverified