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 10151–10175 of 14297 papers

TitleStatusHype
Median-Truncated Nonconvex Approach for Phase Retrieval with Outliers—0
MEDIAPI-SKEL - A 2D-Skeleton Video Database of French Sign Language With Aligned French Subtitles—0
Medical Coding with Biomedical Transformer Ensembles and Zero/Few-shot Learning—0
Medical Dialogue Generation via Intuitive-then-Analytical Differential Diagnosis—0
Medical Image Analysis using Convolutional Neural Networks: A Review—0
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data—0
Medical Image Retrieval Using Pretrained Embeddings—0
Medical Information Retrieval and Interpretation: A Question-Answer based Interaction Model—0
Medical Literature Mining and Retrieval in a Conversational Setting—0
Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances—0
MegaWika: Millions of reports and their sources across 50 diverse languages—0
Melodic Phrase Segmentation By Deep Neural Networks—0
MADial-Bench: Towards Real-world Evaluation of Memory-Augmented Dialogue Generation—0
MemeSequencer: Sparse Matching for Embedding Image Macros—0
MemInsight: Autonomous Memory Augmentation for LLM Agents—0
MEMO: A Deep Network for Flexible Combination of Episodic Memories—0
Memorization to Generalization: Emergence of Diffusion Models from Associative Memory—0
Bridging Personalization and Control in Scientific Personalized Search—0
Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering—0
Memory-Aware and Uncertainty-Guided Retrieval for Multi-Hop Question Answering—0
Memory-Based Deep Neural Attention (mDNA) for Cognitive Multi-Turn Response Retrieval in Task-Oriented Chatbots—0
Memory capacity of neural network models—0
Memory, Consciousness and Large Language Model—0
Memory Consolidation for Contextual Spoken Language Understanding with Dialogue Logistic Inference—0
Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging—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