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 8426–8450 of 14297 papers

TitleStatusHype
CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations—0
Assessing Algorithmic Biases for Musical Version Identification—0
Learned Index with Dynamic—0
KIMERA: Injecting Domain Knowledge into Vacant Transformer Heads—0
Deep Fusion of Multi-attentive Local and Global Features with Higher Efficiency for Image Retrieval—0
Interest-based Item Representation Framework for Recommendation with Multi-Interests Capsule Network—0
In defense of dual-encoders for neural ranking—0
Adaptive Region Pooling for Fine-Grained Representation Learning—0
Seq2Tok: Deep Sequence Tokenizer for Retrieval—0
Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval—0
Contrastive Learning of 3D Shape Descriptor with Dynamic Adversarial Views—0
From Graph Local Embedding to Deep Metric Learning—0
Short-term memory in neural language models—0
Dictionary Learning Under Generative Coefficient Priors with Applications to Compression—0
Self-Supervised Modality-Invariant and Modality-Specific Feature Learning for 3D Objects—0
ASAP DML: Deep Metric Learning with Alternating Sets of Alternating Proxies—0
Regularized Autoencoders for Isometric Representation Learning—0
Sparse Attention with Learning to Hash—0
Zero-Shot Dense Retrieval with Momentum Adversarial Domain Invariant Representation—0
Learning Context-Adapted Video-Text Retrieval by Attending to User Comments—0
Revisiting Locality-Sensitive Binary Codes from Random Fourier Features—0
Rank4Class: Examining Multiclass Classification through the Lens of Learning to Rank—0
Inductive-Biases for Contrastive Learning of Disentangled Representations—0
Graph Similarities and Dual Approach for Sequential Text-to-Image Retrieval—0
Contrastive Pre-training for Zero-Shot Information Retrieval—0
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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