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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 2826–2850 of 9051 papers

TitleStatusHype
An adaptative differential evolution with enhanced diversity and restart mechanismCode0
Facts That MatterCode0
Facilitating bootstrapped and rarefaction-based microbiome diversity analysis with q2-bootsCode0
BAL: Balancing Diversity and Novelty for Active LearningCode0
Motif-Centric Representation Learning for Symbolic MusicCode0
Fact-or-Fair: A Checklist for Behavioral Testing of AI Models on Fairness-Related QueriesCode0
Fair and Diverse DPP-based Data SummarizationCode0
FaceCoresetNet: Differentiable Coresets for Face Set RecognitionCode0
A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural NetworksCode0
Face Manifold: Manifold Learning for Synthetic Face GenerationCode0
Does Writing with Language Models Reduce Content Diversity?Code0
Deep Metric Learning with BIER: Boosting Independent Embeddings RobustlyCode0
Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization FunctionCode0
Adversarial Domain Adaptation for Cross-user Activity Recognition Using Diffusion-based Noise-centred LearningCode0
Multi-Emitter MAP-Elites: Improving quality, diversity and convergence speed with heterogeneous sets of emittersCode0
Hypergraph Clustering for Finding Diverse and Experienced GroupsCode0
Faithful, Unfaithful or Ambiguous? Multi-Agent Debate with Initial Stance for Summary EvaluationCode0
Federated Stain Normalization for Computational PathologyCode0
Exploring the Role of Diversity in Example Selection for In-Context LearningCode0
Multilingual Lexical Simplification via Paraphrase GenerationCode0
Multilingual Neural Machine Translation with Knowledge DistillationCode0
Exploring the Performance-Reproducibility Trade-off in Quality-DiversityCode0
Exploring the Role of Node Diversity in Directed Graph Representation LearningCode0
Deep Learning Models for Atypical Serotonergic Cells RecognitionCode0
Exploring the Evolution of GANs through Quality DiversityCode0
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