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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 4501–4550 of 9051 papers

TitleStatusHype
Neural Story Planning—0
Scaffold-Based Multi-Objective Drug Candidate Optimization—0
Detecting Bone Lesions in X-Ray Under Diverse Acquisition Conditions—0
Objaverse: A Universe of Annotated 3D Objects—0
Urban Scene Semantic Segmentation with Low-Cost Coarse Annotation—0
Calibration-Free Driver Drowsiness Classification based on Manifold-Level AugmentationCode0
Diffusion Probabilistic Models beat GANs on Medical ImagesCode2
APOLLO: An Optimized Training Approach for Long-form Numerical ReasoningCode1
Deep Negative Correlation Classification—0
Multiple Phase Transitions Shape Biodiversity of a Migrating Population—0
RT-1: Robotics Transformer for Real-World Control at ScaleCode3
Pixel is All You Need: Adversarial Trajectory-Ensemble Active Learning for Salient Object Detection—0
A Data Quality Assessment Framework for AI-enabled Wireless Communication—0
Evaluation of Synthetic Datasets for Conversational Recommender Systems—0
BigText-QA: Question Answering over a Large-Scale Hybrid Knowledge Graph—0
Decomposition of the Leinster-Cobbold Diversity Index—0
Cap2Aug: Caption guided Image to Image data Augmentation—0
Invasion and Interaction Determine Population Composition in an Open Evolving System—0
Progressive Multi-view Human Mesh Recovery with Self-Supervision—0
Going beyond richness: Modelling the BEF relationship using species identity, evenness, richness and species interactions via the DImodels R package—0
Frugal Reinforcement-based Active Learning—0
Effective Dynamics of Generative Adversarial Networks—0
MoFusion: A Framework for Denoising-Diffusion-based Motion Synthesis—0
Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection—0
Learning Video Representations from Large Language ModelsCode2
DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue DatasetCode1
Learning Polysemantic Spoof Trace: A Multi-Modal Disentanglement Network for Face Anti-spoofing—0
Learning to Select Prototypical Parts for Interpretable Sequential Data ModelingCode0
Curiosity creates Diversity in Policy Search—0
M3ST: Mix at Three Levels for Speech Translation—0
Self-Supervised Correspondence Estimation via Multiview RegistrationCode1
Improved Beam Search for Hallucination Mitigation in Abstractive Summarization—0
State Space Closure: Revisiting Endless Online Level Generation via Reinforcement LearningCode0
Federated Neural Topic ModelsCode0
On the effectiveness of partial variance reduction in federated learning with heterogeneous dataCode1
HierarchyFL: Heterogeneous Federated Learning via Hierarchical Self-Distillation—0
Towards Generating Diverse Audio Captions via Adversarial Training—0
Brain Tumor Synthetic Data Generation with Adaptive StyleGANsCode0
Unsupervised Fine-Tuning Data Selection for ASR Using Self-Supervised Speech Models—0
Deep Active Learning for Multi-Label Classification of Remote Sensing Images—0
Coevolutionary Framework for Generalized Multimodal Multi-objective OptimizationCode0
An Edge Alignment-based Orientation Selection Method for Neutron Tomography—0
3D-LDM: Neural Implicit 3D Shape Generation with Latent Diffusion Models—0
Few-Shot Specific Emitter Identification via Hybrid Data Augmentation and Deep Metric LearningCode0
Emerging Diversity in a Population of Evolving Intransitive Dice—0
Assessing the Impact of Music Recommendation Diversity on Listeners: A Longitudinal StudyCode0
To think inside the box, or to think out of the box? Scientific discovery via the reciprocation of insights and concepts—0
Scaling Language-Image Pre-training via MaskingCode2
ESG In Corporate Filings: An AI Perspective—0
SinGRAF: Learning a 3D Generative Radiance Field for a Single Scene—0
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