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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 3576–3600 of 9051 papers

TitleStatusHype
SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change DetectionCode1
Adaptive Resource Allocation for Virtualized Base Stations in O-RAN with Online Learning—0
MDSC: Towards Evaluating the Style Consistency Between Music and DanceCode0
What are Public Concerns about ChatGPT? A Novel Self-Supervised Neural Topic Model Tells You—0
Probabilistic Precision and Recall Towards Reliable Evaluation of Generative ModelsCode1
DiverseMotion: Towards Diverse Human Motion Generation via Discrete Diffusion—0
Balancing exploration and exploitation phases in whale optimization algorithm: an insightful and empirical analysis—0
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image SegmentationCode0
Structured Radial Basis Function Network: Modelling Diversity for Multiple Hypotheses Prediction—0
Exploring the Robustness of Human Parsers Towards Common Corruptions—0
Reinforcement Learning with Human Feedback for Realistic Traffic Simulation—0
dacl10k: Benchmark for Semantic Bridge Damage SegmentationCode1
JoTR: A Joint Transformer and Reinforcement Learning Framework for Dialog Policy LearningCode0
Asymmetric double-winged multi-view clustering network for exploring Diverse and Consistent Information—0
Fast Diffusion EM: a diffusion model for blind inverse problems with application to deconvolutionCode1
Fine-Grained Spatiotemporal Motion Alignment for Contrastive Video Representation LearningCode0
MFR-Net: Multi-faceted Responsive Listening Head Generation via Denoising Diffusion Model—0
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural NetworksCode1
Deformation Robust Text Spotting with Geometric Prior—0
Learning Diverse Features in Vision Transformers for Improved GeneralizationCode0
Learning Vision-based Pursuit-Evasion Robot Policies—0
Is the U.S. Legal System Ready for AI's Challenges to Human Values?—0
Denoising Attention for Query-aware User Modeling in Personalized Search—0
CamoFA: A Learnable Fourier-based Augmentation for Camouflage Segmentation—0
Prototype Fission: Closing Set for Robust Open-set Semi-supervised Learning—0
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