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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 4301–4325 of 9051 papers

TitleStatusHype
Improving Low-Resource Sequence Labeling with Knowledge Fusion and Contextual Label Explanations—0
Diffusion-based Target Sampler for Unsupervised Domain Adaptation—0
An Efficient Genetic Algorithm for Discovering Diverse-Frequent Patterns—0
Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Images—0
Diffusion Autoencoders for Few-shot Image Generation in Hyperbolic Space—0
Improving Limited Supervised Foot Ulcer Segmentation Using Cross-Domain Augmentation—0
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation—0
DiffusionAttacker: Diffusion-Driven Prompt Manipulation for LLM Jailbreak—0
Diffusion Adaptation Over Clustered Multitask Networks Based on the Affine Projection Algorithm—0
360U-Former: HDR Illumination Estimation with Panoramic Adapted Vision Transformers—0
Diffusing Differentiable Representations—0
An Efficient Asynchronous Batch Bayesian Optimization Approach for Analog Circuit Synthesis—0
Improving Inversion and Generation Diversity in StyleGAN using a Gaussianized Latent Space—0
DiffusEmp: A Diffusion Model-Based Framework with Multi-Grained Control for Empathetic Response Generation—0
Beyond Accuracy: Statistical Measures and Benchmark for Evaluation of Representation from Self-Supervised Learning—0
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models—0
DiffuDetox: A Mixed Diffusion Model for Text Detoxification—0
Beyond Accuracy Optimization: On the Value of Item Embeddings for Student Job Recommendations—0
A Classification-Based Perspective on GAN Distributions—0
HD Maps are Lane Detection Generalizers: A Novel Generative Framework for Single-Source Domain Generalization—0
Improving negation detection with negation-focused pre-training—0
Beyond-Accuracy: A Review on Diversity, Serendipity and Fairness in Recommender Systems Based on Graph Neural Networks—0
Improving Human Motion Prediction Through Continual Learning—0
DiffTED: One-shot Audio-driven TED Talk Video Generation with Diffusion-based Co-speech Gestures—0
DiffSurf: A Transformer-based Diffusion Model for Generating and Reconstructing 3D Surfaces in Pose—0
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