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 13401–13450 of 14297 papers

TitleStatusHype
Question Answering via Integer Programming over Semi-Structured Knowledge—0
Local Binary Pattern for Word Spotting in Handwritten Historical Document—0
Document Retrieval using Predication Similarity—0
Improving Raw Image Storage Efficiency by Exploiting Similarity—0
Annotation Order Matters: Recurrent Image Annotator for Arbitrary Length Image TaggingCode0
Selective Convolutional Descriptor Aggregation for Fine-Grained Image RetrievalCode1
Supervised Matrix Factorization for Cross-Modality Hashing—0
Radon Features and Barcodes for Medical Image Retrieval via SVM—0
Generating Binary Tags for Fast Medical Image Retrieval Based on Convolutional Nets and Radon Transform—0
Bags of Local Convolutional Features for Scalable Instance SearchCode0
On Reducing the Number of Visual Words in the Bag-of-Features Representation—0
GPU-FV: Realtime Fisher Vector and Its Applications in Video MonitoringCode0
CP-mtML: Coupled Projection multi-task Metric Learning for Large Scale Face Retrieval—0
Intelligent information extraction based on artificial neural network—0
Method of Tibetan Person Knowledge Extraction—0
Scene-driven Retrieval in Edited Videos using Aesthetic and Semantic Deep Features—0
Probabilistic classifiers with low rank indefinite kernels—0
CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard ExamplesCode0
GIFT: A Real-time and Scalable 3D Shape Search Engine—0
Marr Revisited: 2D-3D Alignment via Surface Normal Prediction—0
Deep Image Retrieval: Learning global representations for image searchCode0
The Curious Robot: Learning Visual Representations via Physical Interactions—0
Counting Grid Aggregation for Event Retrieval and Recognition—0
Entity Type Recognition using an Ensemble of Distributional Semantic Models to Enhance Query Understanding—0
Image Captioning with Deep Bidirectional LSTMsCode0
Semi-supervised and Unsupervised Methods for Categorizing Posts in Web Discussion Forums—0
Document Selection in a Distributed Search Engine Architecture—0
Image Retrieval with a Bayesian Model of Relevance Feedback—0
Large Scale Deep Convolutional Neural Network Features Search with Lucene—0
Unsupervised Visual Sense Disambiguation for Verbs using Multimodal EmbeddingsCode0
Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion: Applications to Face Matching, Learning from Unlabeled Videos and 3D-Shape RetrievalCode0
Optimizing the Information Retrieval Trade-off in Data Visualization Using -Divergence—0
Multi-Cue Zero-Shot Learning with Strong Supervision—0
Face Image Analysis using AAM, Gabor, LBP and WD features for Gender, Age, Expression and Ethnicity Classification—0
Learning a Predictable and Generative Vector Representation for ObjectsCode1
CONDITOR1: Topic Maps and DITA labelling tool for textual documents with historical information—0
BreakingNews: Article Annotation by Image and Text Processing—0
Recurrent Neural Network Encoder with Attention for Community Question Answering—0
The Anatomy of a Search and Mining System for Digital Archives—0
Large scale near-duplicate image retrieval using Triples of Adjacent Ranked Features (TARF) with embedded geometric information—0
Generating Natural Questions About an ImageCode0
Learning to Navigate the Energy Landscape—0
Unsupervised Cross-Media Hashing with Structure Preservation—0
Variable-Length Hashing—0
Mitigation Procedures to Rank Experts through Information Retrieval Measures—0
Descriptor transition tables for object retrieval using unconstrained cluttered video acquired using a consumer level handheld mobile device—0
Scalable Image Retrieval by Sparse Product Quantization—0
Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval—0
Memory Recall and Spike Frequency Adaptation—0
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed SystemsCode0
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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