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 9401–9450 of 14297 papers

TitleStatusHype
CLAS: A Machine Learning Enhanced Framework for Exploring Large 3D Design Datasets—0
Class-agnostic Object Detection—0
Class Anchor Margin Loss for Content-Based Image Retrieval—0
CLASS: Enhancing Cross-Modal Text-Molecule Retrieval Performance and Training Efficiency—0
Classification and reconstruction of spatially overlapping phase images using diffractive optical networks—0
Classification and Retrieval of Digital Pathology Scans: A New Dataset—0
Classification in the dark using tactile exploration—0
Classification of Goods Using Text Descriptions With Sentences Retrieval—0
Classification of Medical Images and Illustrations in the Biomedical Literature Using Synergic Deep Learning—0
Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning—0
Classification on Sentence Embeddings for Legal Assistance—0
Classification or Generation? Understanding Paradigm Shift for Knowledge-Intensive Tasks—0
Classification Tree Diagrams in Health Informatics Applications—0
Classifying magnetic resonance image modalities with convolutional neural networks—0
Classifying Peace in Global Media Using RAG and Intergroup Reciprocity—0
Class-RAG: Real-Time Content Moderation with Retrieval Augmented Generation—0
Classroom Video Assessment and Retrieval via Multiple Instance Learning—0
Class-Specific Blind Deconvolutional Phase Retrieval Under a Generative Prior—0
Class-Specific Variational Auto-Encoder for Content-Based Image Retrieval—0
Class Vectors: Embedding representation of Document Classes—0
Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy—0
Clean Image May be Dangerous: Data Poisoning Attacks Against Deep Hashing—0
CLEAR: Cross-Transformers with Pre-trained Language Model is All you need for Person Attribute Recognition and Retrieval—0
Click-Feedback Retrieval—0
Climbing the WOL: Training for Cheaper Inference—0
CLINIQA: A Machine Intelligence Based Clinical Question Answering System—0
CliniQ: A Multi-faceted Benchmark for Electronic Health Record Retrieval with Semantic Match Assessment—0
CLIP2TV: Align, Match and Distill for Video-Text Retrieval—0
CLIP for All Things Zero-Shot Sketch-Based Image Retrieval, Fine-Grained or Not—0
CLIP-GCD: Simple Language Guided Generalized Category Discovery—0
CLIP Multi-modal Hashing: A new baseline CLIPMH—0
CLIP Multi-modal Hashing for Multimedia Retrieval—0
CLIP-PING: Boosting Lightweight Vision-Language Models with Proximus Intrinsic Neighbors Guidance—0
CLIPPING: Distilling CLIP-Based Models With a Student Base for Video-Language Retrieval—0
VITR: Augmenting Vision Transformers with Relation-Focused Learning for Cross-Modal Information Retrieval—0
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?—0
Clique: Spatiotemporal Object Re-identification at the City Scale—0
CLI-RAG: A Retrieval-Augmented Framework for Clinically Structured and Context Aware Text Generation with LLMs—0
CLIRMatrix: A massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval—0
CLIRudit: Cross-Lingual Information Retrieval of Scientific Documents—0
CLOP: Video-and-Language Pre-Training with Knowledge Regularizations—0
Clothes-Changing Person Re-Identification with Feasibility-Aware Intermediary Matching—0
Clothing Retrieval with Visual Attention Model—0
Cloud-Based Real-Time Molecular Screening Platform with MolFormer—0
Cloud detection machine learning algorithms for PROBA-V—0
Cloud Optical Thickness Retrievals Using Angle Invariant Attention Based Deep Learning Models—0
CL-RAG: Bridging the Gap in Retrieval-Augmented Generation with Curriculum Learning—0
CL-ReKD: Cross-lingual Knowledge Distillation for Multilingual Retrieval Question Answering—0
CLTR: An End-to-End, Transformer-Based System for Cell-Level Table Retrieval and Table Question Answering—0
ClueWeb22: 10 Billion Web Documents with Visual and Semantic Information—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