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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 2276–2300 of 9051 papers

TitleStatusHype
One Stack, Diverse Vehicles: Checking Safe Portability of Automated Driving Software—0
Synthetic Data Generation for Augmenting Small Samples—0
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based OptimizationCode0
Scaling Policy Gradient Quality-Diversity with Massive Parallelization via Behavioral Variations—0
Accelerated DC loadflow solver for topology optimization—0
Human-Aligned Skill Discovery: Balancing Behaviour Exploration and Alignment—0
DFPE: A Diverse Fingerprint Ensemble for Enhancing LLM PerformanceCode0
Dynamics of Transient Structure in In-Context Linear Regression Transformers—0
Differentiable Projection-based Learn to Optimize in Wireless Network-Part I: Convex Constrained (Non-)Convex Programming—0
RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution SamplesCode0
Through the Prism of Culture: Evaluating LLMs' Understanding of Indian Subcultures and Traditions—0
Enhancing Synthetic Oversampling for Imbalanced Datasets Using Proxima-Orion Neighbors and q-Gaussian Weighting Technique—0
Making Sense of Data in the Wild: Data Analysis Automation at Scale—0
Data-Efficient Machine Learning Potentials via Difference Vectors Based on Local Atomic Environments—0
IndicMMLU-Pro: Benchmarking Indic Large Language Models on Multi-Task Language Understanding—0
Is It Navajo? Accurate Language Detection in Endangered Athabaskan LanguagesCode0
BAG: Body-Aligned 3D Wearable Asset Generation—0
CP2M: Clustered-Patch-Mixed Mosaic Augmentation for Aerial Image SegmentationCode0
Economic Implications of Corporate Governance and Corporate Social Responsibility: Evidence from Banks in Bangladesh—0
GiantHunter: Accurate detection of giant virus in metagenomic data using reinforcement-learning and Monte Carlo tree searchCode0
FedAlign: Federated Domain Generalization with Cross-Client Feature Alignment—0
Evaluating and Improving Graph to Text Generation with Large Language ModelsCode0
Learning more with the same effort: how randomization improves the robustness of a robotic deep reinforcement learning agent—0
Feature-based Evolutionary Diversity Optimization of Discriminating Instances for Chance-constrained Optimization Problems—0
Neuronal and structural differentiation in the emergence of abstract rules in hierarchically modulated spiking neural networks—0
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