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 7651–7675 of 14297 papers

TitleStatusHype
CL2CM: Improving Cross-Lingual Cross-Modal Retrieval via Cross-Lingual Knowledge Transfer—0
Evaluation-as-a-Service: Overview and Outlook—0
Digging Into Self-Supervised Learning of Feature Descriptors—0
Lensless hyperspectral imaging by Fourier transform spectroscopy for broadband visible light: phase retrieval technique—0
Evaluating Web-as-corpus Topical Document Retrieval with an Index of the OpenDirectory—0
A Retrieval-Augmented Knowledge Mining Method with Deep Thinking LLMs for Biomedical Research and Clinical Support—0
Lesion Search with Self-supervised Learning—0
Less is Less: When Are Snippets Insufficient for Human vs Machine Relevance Estimation?—0
Long-short Term Motion Feature for Action Classification and Retrieval—0
Evaluating Translation Quality and CLIR Performance of Query Sessions—0
Evaluating Transferability in Retrieval Tasks: An Approach Using MMD and Kernel Methods—0
A Retrieval-Augmented Generation Framework for Academic Literature Navigation in Data Science—0
Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability—0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Dimension Projection among Languages based on Pseudo-relevant Documents for Query Translation—0
Lessons from Contextual Bandit Learning in a Customer Support Bot—0
Long-Horizon Planning and Execution with Functional Object-Oriented Networks—0
Less than Few: Self-Shot Video Instance Segmentation—0
Evaluating the Retrieval Component in LLM-Based Question Answering Systems—0
Let Features Decide for Themselves: Feature Mask Network for Person Re-identification—0
Let's have a chat with the EU AI Act—0
Let's measure run time! Extending the IR replicability infrastructure to include performance aspects—0
DINOBot: Robot Manipulation via Retrieval and Alignment with Vision Foundation Models—0
CiteFix: Enhancing RAG Accuracy Through Post-Processing Citation Correction—0
Evaluating the reliability of acoustic speech embeddings—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