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 12851–12900 of 14297 papers

TitleStatusHype
The Solution for the CVPR2024 NICE Image Captioning Challenge—0
PERC: Plan-As-Query Example Retrieval for Underrepresented Code Generation—0
The Spaces of Data, Information, and Knowledge—0
The SpeakIn System Description for CNSRC2022—0
The SP theory of intelligence: an overview—0
The stability of generalized phase retrieval problem over compact groups—0
What Machines See Is Not What They Get: Fooling Scene Text Recognition Models With Adversarial Text Images—0
The State-of-the-Art in Lifelog Retrieval: A Review of Progress at the ACM Lifelog Search Challenge Workshop 2022-24—0
The Statistical Dictionary-based String Matching Problem—0
The style transformer with common knowledge optimization for image-text retrieval—0
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models—0
The Surfer Model with a Hybrid Approach to Ranking the Web Pages—0
Perceptual Visual Interactive Learning—0
The tale of two MS MARCO -- and their unfair comparisons—0
The Tangent Search Engine: Improved Similarity Metrics and Scalability for Math Formula Search—0
The Text Classification Pipeline: Starting Shallow going Deeper—0
The Timing of Lexical Memory Retrievals in Language Production—0
The Tomaco Hybrid Matching Framework for SAWSDL Semantic Web Services—0
Perceptual uniform descriptor and Ranking on manifold: A bridge between image representation and ranking for image retrieval—0
The University of Texas at Dallas HLTRI's Participation in EPIC-QA: Searching for Entailed Questions Revealing Novel Answer Nuggets—0
What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way—0
Online Information Retrieval for Language Learning—0
The Use of Dependency Relation Graph to Enhance the Term Weighting in Question Retrieval—0
The Use of Object Labels and Spatial Prepositions as Keywords in a Web-Retrieval-Based Image Caption Generation System—0
The VISIONE Video Search System: Exploiting Off-the-Shelf Text Search Engines for Large-Scale Video Retrieval—0
The Visual Language of Fabrics—0
Perceptron like Algorithms for Online Learning to Rank—0
People and Places of Historical Europe: Bootstrapping Annotation Pipeline and a New Corpus of Named Entities in Late Medieval Texts—0
The 'who' and 'what' of #diabetes on Twitter—0
The workweek is the best time to start a family -- A Study of GPT-2 Based Claim Generation—0
Online Information Retrieval Evaluation using the STELLA Framework—0
PENTATRON: PErsonalized coNText-Aware Transformer for Retrieval-based cOnversational uNderstanding—0
Pentagon-Match (PMatch): Identification of View-Invariant Planar Feature for Local Feature Matching-Based Homography Estimation—0
Thinking Fast and Slow: Efficient Text-to-Visual Retrieval with Transformers—0
Thinking Like an Annotator: Generation of Dataset Labeling Instructions—0
PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models—0
ThinkSum: Probabilistic reasoning over sets using large language models—0
Think-then-Act: A Dual-Angle Evaluated Retrieval-Augmented Generation—0
What Makes Good In-Context Examples for GPT-3?—0
Thin-Slicing for Pose: Learning to Understand Pose Without Explicit Pose Estimation—0
Peerus Review: a tool for scientific experts finding—0
Thomas Aquinas in the T\"uNDRA: Integrating the Index Thomisticus Treebank into CLARIN-D—0
Thread: A Logic-Based Data Organization Paradigm for How-To Question Answering with Retrieval Augmented Generation—0
Three-Dimensional Bilateral Symmetry Plane Estimation in the Phase Domain—0
Three-Dimensional Coherent Diffractive Imaging of Isolated Faceted Nanostructures—0
Three-Stream Joint Network for Zero-Shot Sketch-Based Image Retrieval—0
What makes visual place recognition easy or hard?—0
Three Things to Know about Deep Metric Learning—0
Three Tiers Neighborhood Graph and Multi-graph Fusion Ranking for Multi-feature Image Retrieval: A Manifold Aspect—0
Three Towers: Flexible Contrastive Learning with Pretrained Image Models—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