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 11051–11100 of 14297 papers

TitleStatusHype
Extractive NarrativeQA with Heuristic Pre-Training—0
ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread—0
Eye Movements Biometrics: A Bibliometric Analysis from 2004 to 2019—0
FABULA: Intelligence Report Generation Using Retrieval-Augmented Narrative Construction—0
FaBULOUS: Fact-checking Based on Understanding of Language Over Unstructured and Structured information—0
Face4RAG: Factual Consistency Evaluation for Retrieval Augmented Generation in Chinese—0
Face Clustering: Representation and Pairwise Constraints—0
Face Image Analysis using AAM, Gabor, LBP and WD features for Gender, Age, Expression and Ethnicity Classification—0
Face Image Retrieval With Attribute Manipulation—0
FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders—0
Face Recognition in the age of CLIP & Billion image datasets—0
Face Retrieval using Frequency Decoded Local Descriptor—0
Face Synthesis (FASY) System for Determining the Characteristics of a Face Image—0
Face Synthesis (FASY) System for Generation of a Face Image from Human Description—0
Faceted classification: management and use—0
Faceted Ranking of Egos in Collaborative Tagging Systems—0
Face Video Retrieval With Image Query via Hashing Across Euclidean Space and Riemannian Manifold—0
Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training—0
Facial Surface Analysis using Iso-Geodesic Curves in Three Dimensional Face Recognition System—0
Facilitating the Manual Annotation of Sounds When Using Large Taxonomies—0
Fact-Aware Multimodal Retrieval Augmentation for Accurate Medical Radiology Report Generation—0
FACT: Examining the Effectiveness of Iterative Context Rewriting for Multi-fact Retrieval—0
Factored couplings in multi-marginal optimal transport via difference of convex programming—0
Factorized Distillation: Training Holistic Person Re-identification Model by Distilling an Ensemble of Partial ReID Models—0
Factory of realities: on the emergence of virtual spatiotemporal structures—0
FACTS About Building Retrieval Augmented Generation-based Chatbots—0
Factual Error Correction for Abstractive Summaries Using Entity Retrieval—0
FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning—0
FAemb: A Function Approximation-Based Embedding Method for Image Retrieval—0
Failing Forward: Improving Generative Error Correction for ASR with Synthetic Data and Retrieval Augmentation—0
FairCLIP: Social Bias Elimination based on Attribute Prototype Learning and Representation Neutralization—0
FaIRCoP: Facial Image Retrieval using Contrastive Personalization—0
FAIR: Fairness-Aware Information Retrieval Evaluation—0
Fairness in Information Access Systems—0
Fairness in Ranking: A Survey—0
FAIR-QR: Enhancing Fairness-aware Information Retrieval through Query Refinement—0
FairRAG: Fair Human Generation via Fair Retrieval Augmentation—0
Fair ranking: a critical review, challenges, and future directions—0
Faithful learning with sure data for lung nodule diagnosis—0
FAKTA: An Automatic End-to-End Fact Checking System—0
FaMTEB: Massive Text Embedding Benchmark in Persian Language—0
FaNS: a Facet-based Narrative Similarity Metric—0
Quantifying Memorization and Retriever Performance in Retrieval-Augmented Vision-Language Models—0
Retrieval-Enhanced Named Entity Recognition—0
Retrieval-Enhanced Visual Prompt Learning for Few-shot Classification—0
RETTA: Retrieval-Enhanced Test-Time Adaptation for Zero-Shot Video Captioning—0
Retrieval-enriched zero-shot image classification in low-resource domains—0
Retrieval & Fine-Tuning for In-Context Tabular Models—0
VDocRAG: Retrieval-Augmented Generation over Visually-Rich Documents—0
Quantifying daseinisation using Shannon entropy—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