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

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Showing 1801–1825 of 14297 papers

TitleStatusHype
Learning an Adaptation Function to Assess Image Visual SimilaritiesCode1
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question AnsweringCode1
LAPIS is a fast web API for massive open virus sequencing databasesCode1
Cross-View Language Modeling: Towards Unified Cross-Lingual Cross-Modal Pre-trainingCode1
One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional MatchingCode1
Optimizing Intermediate Representations of Generative Models for Phase RetrievalCode1
Backpropagation through Combinatorial Algorithms: Identity with Projection WorksCode1
ZusammenQA: Data Augmentation with Specialized Models for Cross-lingual Open-retrieval Question Answering SystemCode1
kNN-Prompt: Nearest Neighbor Zero-Shot InferenceCode1
Tranception: protein fitness prediction with autoregressive transformers and inference-time retrievalCode1
Fast and Light-Weight Answer Text Retrieval in Dialogue SystemsCode1
Cross-Architecture Self-supervised Video Representation LearningCode1
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean MeasuresCode1
End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and ModelsCode1
Optimizing Test-Time Query Representations for Dense RetrievalCode1
EDIN: An End-to-end Benchmark and Pipeline for Unknown Entity Discovery and IndexingCode1
Few-shot Reranking for Multi-hop QA via Language Model PromptingCode1
You Need to Read Again: Multi-granularity Perception Network for Moment Retrieval in VideosCode1
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connectionsCode1
Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural NetworksCode1
SiSPRNet: End-to-End Learning for Single-Shot Phase RetrievalCode1
Towards Tracing Factual Knowledge in Language Models Back to the Training DataCode1
Injecting Domain Adaptation with Learning-to-hash for Effective and Efficient Zero-shot Dense RetrievalCode1
Geo-Localization via Ground-to-Satellite Cross-View Image RetrievalCode1
Language Models with Image Descriptors are Strong Few-Shot Video-Language LearnersCode1
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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