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 3401–3425 of 14297 papers

TitleStatusHype
A Weighted Multi-Criteria Decision Making Approach for Image Captioning—0
Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval—0
Deep API Learning—0
Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization—0
Deep Asymmetric Metric Learning via Rich Relationship Mining—0
Deep Attributes from Context-Aware Regional Neural Codes—0
Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning—0
Dataset of Natural Language Queries for E-Commerce—0
Deep Belief Nets for Topic Modeling—0
Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval—0
Auto-MLM: Improved Contrastive Learning for Self-supervised Multi-lingual Knowledge Retrieval—0
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification—0
A Zero Attention Model for Personalized Product Search—0
DocFinQA: A Long-Context Financial Reasoning Dataset—0
An Analysis on Matching Mechanisms and Token Pruning for Late-interaction Models—0
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data—0
Analyzing Language Learned by an Active Question Answering Agent—0
A Zero-Shot Framework for Sketch based Image Retrieval—0
An Application of Manifold Learning in Global Shape Descriptors—0
Deep Contextualized Biomedical Abbreviation Expansion—0
Deep convolutional embedding for digitized painting clustering—0
Deep Convolutional Features for Image Based Retrieval and Scene Categorization—0
Analyzing Hong Kong's Legal Judgments from a Computational Linguistics point-of-view—0
Alleviating Hallucination in Large Vision-Language Models with Active Retrieval Augmentation—0
DataScout: Automatic Data Fact Retrieval for Statement Augmentation with an LLM-Based Agent—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