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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 4701–4725 of 9051 papers

TitleStatusHype
Differential learning kinetics govern the transition from memorization to generalization during in-context learning—0
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models—0
DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks—0
Prague Dependency Treebank -- Consolidated 1.0—0
Prb-GAN: A Probabilistic Framework for GAN Modelling—0
Predator-prey survival pressure is sufficient to evolve swarming behaviors—0
Predicting Adversarial Examples with High Confidence—0
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation—0
Predicting conversion of mild cognitive impairment to Alzheimer's disease—0
Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s)—0
Predicting Query-Item Relationship using Adversarial Training and Robust Modeling Techniques—0
Predicting retrosynthetic pathways using a combined linguistic model and hyper-graph exploration strategy—0
Predicting scalar diversity with context-driven uncertainty over alternatives—0
Predicting Star Scientists in the Field of Artificial Intelligence: A Machine Learning Approach—0
Predicting Success in Goal-Driven Human-Human Dialogues—0
Predicting the diversity of early epidemic spread on networks—0
Predicting the Skies: A Novel Model for Flight-Level Passenger Traffic Forecasting—0
Prediction of viral spillover risk based on the mass action principle—0
Predictive Analysis for Optimizing Port Operations—0
Predictive modeling and anomaly detection in large-scale web portals through the CAWAL framework—0
Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning—0
Towards Open-Set Myoelectric Gesture Recognition via Dual-Perspective Inconsistency Learning—0
Preference-Conditioned Gradient Variations for Multi-Objective Quality-Diversity—0
Preference-Guided Diffusion for Multi-Objective Offline Optimization—0
Preference Optimization with Multi-Sample Comparisons—0
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