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 9551–9600 of 14297 papers

TitleStatusHype
Comparing Fair Ranking Metrics—0
Comparing Knowledge Sources for Open-Domain Scientific Claim Verification—0
Comparing Neighbors Together Makes it Easy: Jointly Comparing Multiple Candidates for Efficient and Effective Retrieval—0
Comparing persistence diagrams through complex vectors—0
Comparing Probabilistic, Distributional and Transformer-Based Models on Logical Metonymy Interpretation—0
Comparing Traditional and LLM-based Search for Image Geolocation—0
Investigation of Singing Voice Separation for Singing Voice Detection in Polyphonic Music—0
Comparison of the effects of investor attention using search volume data before and after mobile device popularization—0
Comparison Research of Millimeter-Wave/Infrared Co-aperture Reflector Antenna Systems Based on a Specialized Film—0
Compatibility-aware Heterogeneous Visual Search—0
Compensating for Large In-Plane Rotations in Natural Images—0
Competitive Retrieval: Going Beyond the Single Query—0
Complementarity, F-score, and NLP Evaluation—0
Complementing Lexical Retrieval with Semantic Residual Embedding—0
Complete Cross-triplet Loss in Label Space for Audio-visual Cross-modal Retrieval—0
Completion of Missing Labels for Multi-Label Annotation by a Unified Graph Laplacian Regularization—0
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval—0
Complexity-Based Prompting for Multi-Step Reasoning—0
Composed Query Image Retrieval Using Locally Bounded Features—0
Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation—0
Composing Open-domain Vision with RAG for Ocean Monitoring and Conservation—0
Composite Code Sparse Autoencoders for first stage retrieval—0
Composite Correlation Quantization for Efficient Multimodal Retrieval—0
Compositional De-Attention Networks—0
Composition-Aware Image Aesthetics Assessment—0
Composition by Conversation—0
Compound virtual screening by learning-to-rank with gradient boosting decision tree and enrichment-based cumulative gain—0
Comprehending Knowledge Graphs with Large Language Models for Recommender Systems—0
Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling—0
Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering—0
Comprehensive Feature-based Robust Video Fingerprinting Using Tensor Model—0
Comprehensive Review on Semantic Information Retrieval and Ontology Engineering—0
Comprehensive Study on Denoising of Medical Images Utilizing Neural Network Based Auto-Encoder—0
Compressible and Searchable: AI-native Multi-Modal Retrieval System with Learned Image Compression—0
Compressing Sentence Representation via Homomorphic Projective Distillation—0
Compressing Sentence Representation with maximum Coding Rate Reduction—0
Compression of Deep Learning Models for Text: A Survey—0
Compression of Deep Neural Networks for Image Instance Retrieval—0
Compressive Change Retrieval for Moving Object Detection—0
Compressive Phase Retrieval: Optimal Sample Complexity with Deep Generative Priors—0
Compressive Quantization for Fast Object Instance Search in Videos—0
Compressive Shift Retrieval—0
Computational Approaches for App-to-App Retrieval and Design Consistency Check—0
Computationally Bounded Retrieval—0
Computationally Efficient Labeling of Cancer Related Forum Posts by Non-Clinical Text Information Retrieval—0
Computing Lexical Contrast—0
Computing with Cognitive States—0
ComRAG: Retrieval-Augmented Generation with Dynamic Vector Stores for Real-time Community Question Answering in Industry—0
ConaCLIP: Exploring Distillation of Fully-Connected Knowledge Interaction Graph for Lightweight Text-Image Retrieval—0
Concentric network symmetry grasps authors' styles in word adjacency networks—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