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 12451–12500 of 14297 papers

TitleStatusHype
PhysBERT: A Text Embedding Model for Physics Scientific Literature—0
Wasserstein Coupled Graph Learning for Cross-Modal Retrieval—0
Wasserstein distances for evaluating cross-lingual embeddings—0
SynDL: A Large-Scale Synthetic Test Collection for Passage Retrieval—0
SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval—0
Synergistic Approach for Simultaneous Optimization of Monolingual, Cross-lingual, and Multilingual Information Retrieval—0
Synergizing Data Imputation and Electronic Health Records for Advancing Prostate Cancer Research: Challenges, and Practical Applications—0
Synergizing RAG and Reasoning: A Systematic Review—0
Synopses of Movie Narratives: a Video-Language Dataset for Story Understanding—0
Synopses of Movie Narratives: a Video-Language Dataset for Story Understanding—0
Synset Ranking of Hindi WordNet—0
Syntactic Question Abstraction and Retrieval for Data-Scarce Semantic Parsing—0
Syntactic Search by Example—0
SynTF: Synthetic and Differentially Private Term Frequency Vectors for Privacy-Preserving Text Mining—0
Phrase2VecGLM: Neural generalized language model--based semantic tagging for complex query reformulation in medical IR—0
SynthBio: A Case Study in Human-AI Collaborative Curation of Text Datasets—0
Synthesizing Conversations from Unlabeled Documents using Automatic Response Segmentation—0
PhotoChat: A Human-Human Dialogue Dataset with Photo Sharing Behavior for Joint Image-Text Modeling—0
Synthetic Cross-language Information Retrieval Training Data—0
Synthetic Interlocutors. Experiments with Generative AI to Prolong Ethnographic Encounters—0
Synthetic Latent Fingerprint Generator—0
Synthetic Multimodal Question Generation—0
ZEBRA: Z-order Curve-based Event Retrieval Approach to Efficiently Explore Automotive Data—0
Synthetic Target Domain Supervision for Open Retrieval QA—0
Phonetic-and-Semantic Embedding of Spoken Words with Applications in Spoken Content Retrieval—0
SynthScribe: Deep Multimodal Tools for Synthesizer Sound Retrieval and Exploration—0
System Analysis And Design For Multimedia Retrieval Systems—0
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?—0
On Ranking Consistency of Pre-ranking Stage—0
System Description of CITlab's Recognition & Retrieval Engine for ICDAR2017 Competition on Information Extraction in Historical Handwritten Records—0
T^2K^2: The Twitter Top-K Keywords Benchmark—0
Phoneme-retrieval; voice recognition; vowels recognition—0
Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation—0
Watch Your Step: Optimal Retrieval for Continual Learning at Scale—0
TABi: Type-Aware Bi-encoders for End-to-End Entity Retrieval—0
Phase transitions in Restricted Boltzmann Machines with generic priors—0
Table of Content detection using Machine Learning—0
Phase transition of descending phase retrieval algorithms—0
OMGM: Orchestrate Multiple Granularities and Modalities for Efficient Multimodal Retrieval—0
Table Retrieval Does Not Necessitate Table-specific Model Design—0
Phase retrieval with semi-algebraic and ReLU neural network priors—0
Phase retrieval with rank d measurements -- descending algorithms phase transitions—0
Table Structure Recognition with Conditional Attention—0
Phase retrieval with physics informed zero-shot learning—0
Phase retrieval with complexity guidance—0
tabulapdf: An R Package to Extract Tables from PDF Documents—0
Tabular Embedding Model (TEM): Finetuning Embedding Models For Tabular RAG Applications—0
Watermark Retrieval from 3D Printed Objects via Convolutional Neural Networks—0
Tackling Situated Multi-Modal Task-Oriented Dialogs with a Single Transformer Model—0
Watermark retrieval from 3D printed objects via synthetic data training—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