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 5751–5800 of 14297 papers

TitleStatusHype
Toward Real-Time Image Annotation Using Marginalized Coupled Dictionary LearningCode0
OPI at SemEval 2023 Task 1: Image-Text Embeddings and Multimodal Information Retrieval for Visual Word Sense Disambiguation—0
Tempo vs. Pitch: understanding self-supervised tempo estimationCode1
Perspectives on Large Language Models for Relevance JudgmentCode0
Deep Metric Multi-View Hashing for Multimedia Retrieval—0
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study—0
Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report—0
Noisy Correspondence Learning with Meta Similarity CorrectionCode1
TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval—0
Open-TransMind: A New Baseline and Benchmark for 1st Foundation Model Challenge of Intelligent TransportationCode1
Unicom: Universal and Compact Representation Learning for Image RetrievalCode2
Rethinking Dense Retrieval's Few-Shot AbilityCode1
SketchANIMAR: Sketch-based 3D Animal Fine-Grained Retrieval—0
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition—0
FALQU: Finding Answers to Legal QuestionsCode0
RECLIP: Resource-efficient CLIP by Training with Small Images—0
Are Local Features All You Need for Cross-Domain Visual Place Recognition?Code1
A Phoneme-Informed Neural Network Model for Note-Level Singing Transcription—0
Soft Dynamic Time Warping for Multi-Pitch Estimation and Beyond—0
LADER: Log-Augmented DEnse Retrieval for Biomedical Literature Search—0
Delving into E-Commerce Product Retrieval with Vision-Language Pre-training—0
WebBrain: Learning to Generate Factually Correct Articles for Queries by Grounding on Large Web CorpusCode1
CAVL: Learning Contrastive and Adaptive Representations of Vision and Language—0
Learning to Tokenize for Generative RetrievalCode1
Unsupervised Multi-Criteria Adversarial Detection in Deep Image Retrieval—0
AI-assisted Automated Workflow for Real-time X-ray Ptychography Data Analysis via Federated Resources—0
Editable User Profiles for Controllable Text RecommendationCode0
MphayaNER: Named Entity Recognition for TshivendaCode0
LSGDDN-LCD: An Appearance-based Loop Closure Detection using Local Superpixel Grid Descriptors and Incremental Dynamic Nodes—0
DATE: Domain Adaptive Product Seeker for E-commerceCode0
Generative Recommendation: Towards Next-generation Recommender ParadigmCode1
From Retrieval to Generation: Efficient and Effective Entity Set Expansion—0
T2Ranking: A large-scale Chinese Benchmark for Passage RankingCode1
Robust Calibrate Proxy Loss for Deep Metric Learning—0
Self-Supervised Video Similarity LearningCode1
Exposing and Mitigating Spurious Correlations for Cross-Modal RetrievalCode0
R^2Former: Unified Retrieval and Reranking Transformer for Place RecognitionCode0
Noise-Robust Dense Retrieval via Contrastive Alignment Post Training—0
Patch-aware Batch Normalization for Improving Cross-domain Robustness—0
Evidentiality-aware Retrieval for Overcoming Abstractiveness in Open-Domain Question Answering—0
Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search—0
CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrieval—0
Context-Aware Classification of Legal Document Pages—0
PWESuite: Phonetic Word Embeddings and Tasks They FacilitateCode1
LogoNet: a fine-grained network for instance-level logo sketch retrievalCode0
Ericson: An Interactive Open-Domain Conversational Search Agent—0
Efficient OCR for Building a Diverse Digital HistoryCode1
AToMiC: An Image/Text Retrieval Test Collection to Support Multimedia Content CreationCode3
Rethinking the Role of Token Retrieval in Multi-Vector RetrievalCode1
Form-NLU: Dataset for the Form Natural Language UnderstandingCode1
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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