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 4251–4275 of 14297 papers

TitleStatusHype
Cross-Modal Center Loss for 3D Cross-Modal Retrieval—0
Adaptive Schema-aware Event Extraction with Retrieval-Augmented Generation—0
Cross-modal Center Loss—0
A unified Neural Network Approach to E-CommerceRelevance Learning—0
A Multi-strategy Query Processing Approach for Biomedical Question Answering: USTB\_PRIR at BioASQ 2017 Task 5B—0
Evaluation Evaluation a Monte Carlo study—0
Evaluation of baseline information retrieval for Polish open-domain Question Answering system—0
Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieval—0
A Multi-Source Retrieval Question Answering Framework Based on RAG—0
Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization—0
A Unified Model for Video Understanding and Knowledge Embedding with Heterogeneous Knowledge Graph Dataset—0
Accelerating Code Search with Deep Hashing and Code Classification—0
Evaluation by Association: A Systematic Study of Quantitative Word Association Evaluation—0
Cross-Modal Adaptive Dual Association for Text-to-Image Person Retrieval—0
Cross-Modal Adapter: Parameter-Efficient Transfer Learning Approach for Vision-Language Models—0
A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios—0
Cross-Modal 3D Representation with Multi-View Images and Point Clouds—0
A Multi-Resolution Word Embedding for Document Retrieval from Large Unstructured Knowledge Bases—0
Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home—0
Évaluation des capacités de réponse de larges modèles de langage (LLM) pour des questions d'historiens—0
Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval—0
Cross-media Similarity Metric Learning with Unified Deep Networks—0
A unified framework of predicting binary interestingness of images based on discriminant correlation analysis and multiple kernel learning—0
Evaluating Transferability in Retrieval Tasks: An Approach Using MMD and Kernel Methods—0
Cross-Media Scientific Research Achievements Retrieval Based on Deep Language Model—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