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 7376–7400 of 14297 papers

TitleStatusHype
Adaptive Margin Diversity Regularizer for handling Data Imbalance in Zero-Shot SBIR—0
A Case Study on the Impact of Similarity Measure on Information Retrieval based Software Engineering Tasks—0
How Vital is the Jurisprudential Relevance: Law Article Intervened Legal Case Retrieval and Matching—0
How User Language Affects Conflict Fatality Estimates in ChatGPT—0
CoVLR: Coordinating Cross-Modal Consistency and Intra-Modal Structure for Vision-Language Retrieval—0
Learning Dynamic Classes of Events using Stacked Multilayer Perceptron Networks—0
Learning Effective Binary Visual Representations with Deep Networks—0
How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval—0
Learning Efficient Representations for Image-Based Patent Retrieval—0
Learning Embeddings for Product Visual Search with Triplet Loss and Online Sampling—0
Learning Embodied Semantics via Music and Dance Semiotic Correlations—0
COVIDLies: Detecting COVID-19 Misinformation on Social Media—0
Enhancing Retrieval-Augmented Audio Captioning with Generation-Assisted Multimodal Querying and Progressive Learning—0
Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages—0
How to Train Triplet Networks with 100K Identities?—0
Learning Federated Representations and Recommendations with Limited Negatives—0
Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation—0
How to Search the Internet Archive Without Indexing It—0
COVID-19 Literature Mining and Retrieval using Text Mining Approaches—0
How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models?—0
Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders—0
Learning From Weights: A Cost-Sensitive Approach For Ad Retrieval—0
How to Read Paintings: Semantic Art Understanding with Multi-Modal Retrieval—0
Learning Geodesic-Aware Local Features from RGB-D Images—0
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature—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