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 4551–4575 of 14297 papers

TitleStatusHype
Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem—0
Fact-Aware Multimodal Retrieval Augmentation for Accurate Medical Radiology Report Generation—0
Convex and Scalable Weakly Labeled SVMs—0
Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report—0
A Triplet-loss Dilated Residual Network for High-Resolution Representation Learning in Image Retrieval—0
A Trio Neural Model for Dynamic Entity Relatedness Ranking—0
A Massively Parallel Associative Memory Based on Sparse Neural Networks—0
Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training—0
Adaptive Cross Batch Normalization for Metric Learning—0
Conversation Initiation by Diverse News Contents Introduction—0
Faceted Ranking of Egos in Collaborative Tagging Systems—0
Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Language Retrieval—0
A Semantic Search Pipeline for Causality-driven Adhoc Information Retrieval—0
Face Video Retrieval With Image Query via Hashing Across Euclidean Space and Riemannian Manifold—0
Facial Surface Analysis using Iso-Geodesic Curves in Three Dimensional Face Recognition System—0
Conversational Text Extraction with Large Language Models Using Retrieval-Augmented Systems—0
Conversational Search with Mixed-Initiative - Asking Good Clarification Questions backed-up by Passage Retrieval—0
A Transformer-Based Visual Piano Transcription Algorithm—0
Conversational Search with Mixed-Initiative -- Asking Good Clarification Questions backed-up by Passage Retrieval—0
Conversational Search for Learning Technologies—0
A Transformer Based Pitch Sequence Autoencoder with MIDI Augmentation—0
A MapReduce Approach to Effectively Utilize Long Context Information in Retrieval Augmented Language Models—0
Conversational Search -- A Report from Dagstuhl Seminar 19461—0
Conversational Recommendation as Retrieval: A Simple, Strong Baseline—0
A Transformer-based Embedding Model for Personalized Product Search—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