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 9351–9375 of 14297 papers

TitleStatusHype
Information Ranking Using Optimum-Path Forest—0
NeuralNDCG: Direct Optimisation of a Ranking Metric via Differentiable Relaxation of SortingCode1
Overview of the TREC 2020 deep learning trackCode1
Win-Fail Action RecognitionCode0
Learning Intra-Batch Connections for Deep Metric LearningCode1
Colored Kimia Path24 Dataset: Configurations and Benchmarks with Deep Embeddings—0
PAQ: 65 Million Probably-Asked Questions and What You Can Do With ThemCode1
Supporting search engines with knowledge and context—0
Exploring Classic and Neural Lexical Translation Models for Information Retrieval: Interpretability, Effectiveness, and Efficiency BenefitsCode1
Exploring the Impact of Noise on Hybrid Inversion of PROSAIL RTM on Sentinel-2 DataCode1
Less is More: ClipBERT for Video-and-Language Learning via Sparse SamplingCode1
DEEPF0: End-To-End Fundamental Frequency Estimation for Music and Speech Signals—0
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text SupervisionCode2
Training Vision Transformers for Image RetrievalCode1
VINS: Visual Search for Mobile User Interface DesignCode1
Biomedical Question Answering: A Survey of Approaches and Challenges—0
Fashion Focus: Multi-modal Retrieval System for Video Commodity Localization in E-commerce—0
Efficient Retrieval Augmented Generation from Unstructured Knowledge for Task-Oriented DialogCode0
Content Placement in Networks of Similarity Caches—0
NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application—0
Rethinking the Optimization of Average Precision: Only Penalizing Negative Instances before Positive Ones is EnoughCode1
Telling the What while Pointing to the Where: Multimodal Queries for Image Retrieval—0
User Engagement Prediction for Clarification in SearchCode0
An Efficient Framework for Zero-Shot Sketch-Based Image Retrieval—0
Multi-level Distance Regularization for Deep Metric LearningCode1
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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