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 3151–3200 of 14297 papers

TitleStatusHype
Learning Spatial-context-aware Global Visual Feature Representation for Instance Image RetrievalCode0
Automatic Instrument Recognition in Polyphonic Music Using Convolutional Neural NetworksCode0
Learning semantic sentence representations from visually grounded language without lexical knowledgeCode0
Learning Retrieval Augmentation for Personalized Dialogue GenerationCode0
Learning Self-Regularized Adversarial Views for Self-Supervised Vision TransformersCode0
A Dataset and Framework for Learning State-invariant Object RepresentationsCode0
Learning Ordered Representations with Nested DropoutCode0
Automatic Generation of Model and Data Cards: A Step Towards Responsible AICode0
Automatic Generation of Fashion Images using Prompting in Generative Machine Learning ModelsCode0
Learning Permutation-Invariant Embeddings for Description Logic ConceptsCode0
Analysing the Robustness of Dual Encoders for Dense Retrieval Against MisspellingsCode0
Learning to Prune in Metric and Non-Metric SpacesCode0
Analysing the Resourcefulness of the Paragraph for Precedence RetrievalCode0
Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text RetrievalCode0
Combining Lexical and Dense Retrieval for Computationally Efficient Multi-hop Question AnsweringCode0
Automatic Data Retrieval for Cross Lingual SummarizationCode0
Learning Genomic Sequence Representations using Graph Neural Networks over De Bruijn GraphsCode0
Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual FeaturesCode0
Domain-Aware SE Network for Sketch-based Image Retrieval with Multiplicative Euclidean Margin SoftmaxCode0
Learning Dynamic Author Representations with Temporal Language ModelsCode0
Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality GapCode0
Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question AnsweringCode0
Automatic Context Pattern Generation for Entity Set ExpansionCode0
Learning Dual Retrieval Module for Semi-supervised Relation ExtractionCode0
Learning Disentangled Representations of Texts with Application to Biomedical AbstractsCode0
Learning Discriminative 3D Shape Representations by View Discerning NetworksCode0
Learning Disentangled Representations via Mutual Information EstimationCode0
Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion: Applications to Face Matching, Learning from Unlabeled Videos and 3D-Shape RetrievalCode0
An All-MLP Sequence Modeling Architecture That Excels at CopyingCode0
CNTLS: A Benchmark Dataset for Abstractive or Extractive Chinese Timeline SummarizationCode0
Learning Deep Local Features With Multiple Dynamic Attentions for Large-Scale Image RetrievalCode0
Ada-Retrieval: An Adaptive Multi-Round Retrieval Paradigm for Sequential RecommendationsCode0
Learning Deep Nearest Neighbor Representations Using Differentiable Boundary TreesCode0
Learning Compressed Sentence Representations for On-Device Text ProcessingCode0
Learning Contextualized Document Representations for Healthcare Answer RetrievalCode0
Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food ImagesCode0
Learning Deep Representations of Fine-grained Visual DescriptionsCode0
Automated Few-shot Classification with Instruction-Finetuned Language ModelsCode0
Learning Character-Agnostic Motion for Motion Retargeting in 2DCode0
Learning compact binary descriptors with unsupervised deep neural networksCode0
Learning Compatible Multi-Prize Subnetworks for Asymmetric RetrievalCode0
Automated crater shape retrieval using weakly-supervised deep learningCode0
Learning Audio Concepts from Counterfactual Natural LanguageCode0
Learning Attractor Dynamics for Generative MemoryCode0
The iMet Collection 2019 Challenge DatasetCode0
Learning Complex Basis Functions for Invariant Representations of AudioCode0
Learning Metrics from Teachers: Compact Networks for Image EmbeddingCode0
Learning to Rank Context for Named Entity Recognition Using a Synthetic DatasetCode0
Learned k-NN Distance EstimationCode0
Adaptive Testing of Computer Vision ModelsCode0
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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