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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 151–175 of 9051 papers

TitleStatusHype
DualAnoDiff: Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image GenerationCode2
Effective Data Augmentation With Diffusion ModelsCode2
Face2Diffusion for Fast and Editable Face PersonalizationCode2
Freeform Body Motion Generation from SpeechCode2
3DGen: Triplane Latent Diffusion for Textured Mesh GenerationCode2
Diffusion Models Beat GANs on Image SynthesisCode2
A Closer Look into Mixture-of-Experts in Large Language ModelsCode2
Anomaly Detection via Reverse Distillation from One-Class EmbeddingCode2
DiffusionLight: Light Probes for Free by Painting a Chrome BallCode2
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative DataCode2
DivPrune: Diversity-based Visual Token Pruning for Large Multimodal ModelsCode2
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-TrainingCode2
Diffusion Models for Molecules: A Survey of Methods and TasksCode2
AnySat: One Earth Observation Model for Many Resolutions, Scales, and ModalitiesCode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image ClassificationCode2
DiffuSeq: Sequence to Sequence Text Generation with Diffusion ModelsCode2
DiffTF++: 3D-aware Diffusion Transformer for Large-Vocabulary 3D GenerationCode2
Diffusion Bridge Implicit ModelsCode2
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-MakingCode2
Enhancing Sample Efficiency and Exploration in Reinforcement Learning through the Integration of Diffusion Models and Proximal Policy OptimizationCode2
EVA3D: Compositional 3D Human Generation from 2D Image CollectionsCode2
Explaining Machine Learning Classifiers through Diverse Counterfactual ExplanationsCode2
Exploring the Effect of Dataset Diversity in Self-Supervised Learning for Surgical Computer VisionCode2
DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Iterative Diffusion-Based RefinementCode2
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