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 11151–11200 of 14297 papers

TitleStatusHype
Language Features Matter: Effective Language Representations for Vision-Language Tasks—0
Learning Representations and Agents for Information Retrieval—0
CFO: A Framework for Building Production NLP Systems—0
Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based ChatbotsCode0
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training—0
Semantic Source Code Search: A Study of the Past and a Glimpse at the Future—0
Hamming Sentence Embeddings for Information Retrieval—0
DeepHuMS: Deep Human Motion Signature for 3D Skeletal Sequences—0
Harmonized Multimodal Learning with Gaussian Process Latent Variable ModelsCode0
Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation—0
Shape-Aware Complementary-Task Learning for Multi-Organ SegmentationCode0
Linking Graph Entities with Multiplicity and Provenance—0
Getting To Know You: User Attribute Extraction from DialoguesCode0
Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA SystemCode0
An Effective Domain Adaptive Post-Training Method for BERT in Response SelectionCode0
AmazonQA: A Review-Based Question Answering TaskCode0
SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing—0
Online Continual Learning with Maximally Interfered RetrievalCode0
Unsupervised Neural Quantization for Compressed-Domain Similarity SearchCode0
Knowledge Aware Semantic Concept Expansion for Image-Text Matching—0
Deep Triplet Neural Networks with Cluster-CCA for Audio-Visual Cross-modal RetrievalCode0
Audio-Visual Embedding for Cross-Modal MusicVideo Retrieval through Supervised Deep CCA—0
Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media ImagesCode0
Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings—0
Semi Supervised Phrase Localization in a Bidirectional Caption-Image Retrieval Framework—0
Text mining policy: Classifying forest and landscape restoration policy agenda with neural information retrieval—0
Metric Learning With HORDE: High-Order Regularizer for Deep EmbeddingsCode0
Hierarchy-of-Visual-Words: a Learning-based Approach for Trademark Image RetrievalCode1
Location Field Descriptors: Single Image 3D Model Retrieval in the Wild—0
View N-gram Network for 3D Object Retrieval—0
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language TasksCode1
Unsupervised Context Retrieval for Long-tail Entities—0
Local versus Global Strategies in Social Query Expansion—0
A Fast Content-Based Image Retrieval Method Using Deep Visual Features—0
Learning a Unified Embedding for Visual Search at Pinterest—0
ABD-Net: Attentive but Diverse Person Re-IdentificationCode0
L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention—0
On the Merge of k-NN GraphCode0
Robust Document Representations for Cross-Lingual Information Retrieval in Low-Resource Settings—0
Lexical Representation \& Retrieval on Monolingual Interpretative text production—0
Exploring Transfer Learning and Domain Data Selection for the Biomedical Translation—0
Central Similarity Quantization for Efficient Image and Video RetrievalCode0
KiloGrams: Very Large N-Grams for Malware ClassificationCode0
LasigeBioTM at MEDIQA 2019: Biomedical Question Answering using Bidirectional Transformers and Named Entity Recognition—0
ArbEngVec : Arabic-English Cross-Lingual Word Embedding Model—0
IIT-KGP at MEDIQA 2019: Recognizing Question Entailment using Sci-BERT stacked with a Gradient Boosting Classifier—0
ARS\_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System—0
Segmentation for Domain Adaptation in Arabic—0
Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question AnsweringCode1
Grammatical-Error-Aware Incorrect Example Retrieval System for Learners of Japanese as a Second Language—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