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 12551–12600 of 14297 papers

TitleStatusHype
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution—0
Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database—0
A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-RankingCode0
Camera Style Adaptation for Person Re-identificationCode0
Discriminative Learning of Open-Vocabulary Object Retrieval and Localization by Negative Phrase Augmentation—0
Separating Self-Expression and Visual Content in Hashtag SupervisionCode0
Production Ready Chatbots: Generate if not Retrieve—0
Scalable Object Detection for Stylized Objects—0
Balancing Speed and Quality in Online Learning to Rank for Information RetrievalCode0
HashGAN:Attention-aware Deep Adversarial Hashing for Cross Modal Retrieval—0
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)Code0
Neural Ranking Models with Multiple Document Fields—0
Paper evolution graph: Multi-view structural retrieval for academic literature—0
Supervised Hashing with End-to-End Binary Deep Neural Network—0
A Deep Relevance Matching Model for Ad-hoc RetrievalCode0
End-to-End Supervised Product Quantization for Image Search and Retrieval—0
Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce—0
Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models—0
ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks—0
Learning Deep Representations of Medical Images using Siamese CNNs with Application to Content-Based Image Retrieval—0
The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching—0
Let Features Decide for Themselves: Feature Mask Network for Person Re-identification—0
Disentangling Factors of Variation by Mixing Them—0
Real-time fMRI neurofeedback of the mediodorsal and anterior thalamus enhances correlation between thalamic BOLD activity and alpha EEG rhythm—0
Kill Two Birds with One Stone: Weakly-Supervised Neural Network for Image Annotation and Tag Refinement—0
A Genetic Algorithm Approach for ImageRepresentation Learning through Color Quantization—0
Repeatability Is Not Enough: Learning Affine Regions via DiscriminabilityCode1
Learning SO(3) Equivariant Representations with Spherical CNNsCode1
Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models—0
A Revisit on Deep Hashings for Large-scale Content Based Image Retrieval—0
Remedies against the Vocabulary Gap in Information Retrieval—0
An Encoder-Decoder Framework Translating Natural Language to Database Queries—0
CMU LiveMedQA at TREC 2017 LiveQA: A Consumer Health Question Answering System—0
Dual-Path Convolutional Image-Text Embeddings with Instance LossCode0
On consistent vertex nomination schemes—0
Joint Gaussian Processes for Biophysical Parameter Retrieval—0
Aggregated Wasserstein Metric and State Registration for Hidden Markov Models—0
A distributed system for SearchOnMath based on the Microsoft BizSpark program—0
RDF2Vec: RDF Graph Embeddings and Their ApplicationsCode1
Joint Sentiment/Topic Modeling on Text Data Using Boosted Restricted Boltzmann Machine—0
RubyStar: A Non-Task-Oriented Mixture Model Dialog System—0
Fidelity-Weighted Learning—0
Unsupervised Learning of Semantic Audio Representations—0
The NoXi database: multimodal recordings of mediated novice-expert interactions—0
Fine-tuning CNN Image Retrieval with No Human AnnotationCode1
Optimization of phase retrieval in the Fresnel domain by the modified Gerchberg-Saxton algorithmCode0
Set-to-Set Hashing with Applications in Visual Recognition—0
Hi, how can I help you?: Automating enterprise IT support help desks—0
Automatic Query Image Disambiguation for Content-Based Image RetrievalCode0
使用查詢意向探索與類神經網路於語音文件檢索之研究 (Exploring Query Intent and Neural Network modeling Techniques for Spoken Document Retrieval) [In Chinese]—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