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 4451–4475 of 14297 papers

TitleStatusHype
Attribute-Guided Pedestrian Retrieval: Bridging Person Re-ID with Internal Attribute Variability—0
A Method of Passage-Based Document Retrieval in Question Answering System—0
Attribute-Guided Network for Cross-Modal Zero-Shot Hashing—0
Debiasing Gender Bias in Information Retrieval Models—0
Correlations strike back (again): the case of associative memory retrieval—0
Correlation Hashing Network for Efficient Cross-Modal Retrieval—0
A Method for Multi-Hop Question Answering on Persian Knowledge Graph—0
Correlation between Similarity Measures for Inter-Language Linked Wikipedia Articles—0
Correlating and Cross-linking Knowledge Threads in Informledge System for Creating New Knowledge—0
Beyond Prompting: An Efficient Embedding Framework for Open-Domain Question Answering—0
Adaptive Graph-based Generalized Regression Model for Unsupervised Feature Selection—0
Exploring Fine-tuning Techniques for Pre-trained Cross-lingual Models via Continual Learning—0
Exploring Inherent Properties of the Monophonic Melody of Songs—0
Corpus Wide Argument Mining -- a Working Solution—0
Attonsecond Streaking Phase Retrieval Via Deep Learning Methods—0
RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Network—0
A Meta-embedding-based Ensemble Approach for ICD Coding Prediction—0
Attentive Representation Learning with Adversarial Training for Short Text Clustering—0
Corpus-informed Retrieval Augmented Generation of Clarifying Questions—0
A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models—0
Corpus COFLA: A research corpus for the Computational study of Flamenco Music—0
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval—0
Exploring Federated Self-Supervised Learning for General Purpose Audio Understanding—0
Exploring Knowledge Boundaries in Large Language Models for Retrieval Judgment—0
Exploring new Approaches for Information Retrieval through Natural Language Processing—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