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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 2776–2800 of 9051 papers

TitleStatusHype
Diversity-Driven Learning: Tackling Spurious Correlations and Data Heterogeneity in Federated Models—0
Diversity of Thought Improves Reasoning Abilities of LLMs—0
Diversity of Transformer Layers: One Aspect of Parameter Scaling Laws—0
Diversity of What? On the Different Conceptualizations of Diversity in Recommender Systems—0
Cancer-Net PCa-Data: An Open-Source Benchmark Dataset for Prostate Cancer Clinical Decision Support using Synthetic Correlated Diffusion Imaging Data—0
Diversity-Oriented Data Augmentation with Large Language Models—0
Diversity Over Quantity: A Lesson From Few Shot Relation Classification—0
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis—0
Diversity Preference-Aware Link Recommendation for Online Social Networks—0
Diversity Preferences, Affirmative Action and Choice Rules—0
Diversity-Preserving K-Armed Bandits, Revisited—0
Diversity Progress for Goal Selection in Discriminability-Motivated RL—0
Diversity-Promoting Bayesian Learning of Latent Variable Models—0
Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation—0
Diversity-Promoting Ensemble for Medical Image Segmentation—0
Diversity-Driven Generative Dataset Distillation Based on Diffusion Model with Self-Adaptive Memory—0
Diversity-Promoting Human Motion Interpolation via Conditional Variational Auto-Encoder—0
Diversity Promoting Online Sampling for Streaming Video Summarization—0
Diversity regularization in deep ensembles—0
Diversity Regularized Adversarial Learning—0
Diversity Regularized Interests Modeling for Recommender Systems—0
Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification—0
Diversity-Rewarded CFG Distillation—0
Diversity-Robust Acoustic Feature Signatures Based on Multiscale Fractal Dimension for Similarity Search of Environmental Sounds—0
Burn After Reading: Online Adaptation for Cross-domain Streaming Data—0
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