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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 8551–8575 of 9051 papers

TitleStatusHype
Diversifying Reply Suggestions using a Matching-Conditional Variational Autoencoder—0
Advanced Signal Processing Techniques for Fixed and Mobile Satellite Communications—0
Diversifying Sparsity Using Variational Determinantal Point Processes—0
Advanced Framework for Animal Sound Classification With Features Optimization—0
Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer—0
Diversify Question Generation with Continuous Content Selectors and Question Type Modeling—0
Planner3D: LLM-enhanced graph prior meets 3D indoor scene explicit regularization—0
Composite Indicator-Guided Infilling Sampling for Expensive Multi-Objective Optimization—0
DiversiTree: A New Method to Efficiently Compute Diverse Sets of Near-Optimal Solutions to Mixed-Integer Optimization Problems—0
Diversity-Achieving Slow-DropBlock Network for Person Re-Identification—0
Embracing Diversity: A Multi-Perspective Approach with Soft Labels—0
Diversity Analysis for Indoor Terahertz Communication Systems under Small-Scale Fading—0
Diversity and bias in audio captioning datasets—0
Diversity and coevolutionary dynamics in high-dimensional phenotype spaces—0
Diversity and Consistency: Exploring Visual Question-Answer Pair Generation—0
Diversity and degrees of freedom in regression ensembles—0
Diversity and Depth in Per-Example Routing Models—0
Diversity and Diffusion: Observations on Synthetic Image Distributions with Stable Diffusion—0
adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads—0
Diversity and Inclusion in AI for Recruitment: Lessons from Industry Workshop—0
Diversity and Inclusion in Artificial Intelligence—0
Diversity and Inclusion Index with Networks and Similarity: Analysis and its Application—0
Diversity and Inclusion Metrics in Subset Selection—0
Diversity and Language Technology: How Techno-Linguistic Bias Can Cause Epistemic Injustice—0
Diversity and Multiplexing for Continuous Aperture Array (CAPA)-Based Communications—0
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