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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 5051–5075 of 9051 papers

TitleStatusHype
RMD: A Simple Baseline for More General Human Motion Generation via Training-free Retrieval-Augmented Motion Diffuse—0
RNE: A Scalable Network Embedding for Billion-scale Recommendation—0
Road detection via a dual-task network based on cross-layer graph fusion modules—0
Robo-Instruct: Simulator-Augmented Instruction Alignment For Finetuning Code LLMs—0
RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation—0
RobotFingerPrint: Unified Gripper Coordinate Space for Multi-Gripper Grasp Synthesis and Transfer—0
Robo-Troj: Attacking LLM-based Task Planners—0
Robust Allocations with Diversity Constraints—0
Robust Deep Learning Based Sentiment Classification of Code-Mixed Text—0
Robust Deep Learning Ensemble against Deception—0
Robust Deep Learning Models Against Semantic-Preserving Adversarial Attack—0
Robust Federated Learning on Edge Devices with Domain Heterogeneity—0
Robust Fraud Detection via Supervised Contrastive Learning—0
Robust Hierarchical Patterns for identifying MDD patients: A Multisite Study—0
Robust Invariant Representation Learning by Distribution Extrapolation—0
Robust Memory Augmentation by Constrained Latent Imagination—0
Robust Model Predictive Control for nonlinear discrete-time systems using iterative time-varying constraint tightening—0
Robustness for Free: Quality-Diversity Driven Discovery of Agile Soft Robotic Gaits—0
Robustness-Guided Image Synthesis for Data-Free Quantization—0
Robustness-via-Synthesis: Robust Training with Generative Adversarial Perturbations—0
Robust portfolio optimization for recommender systems considering uncertainty of estimated statistics—0
Robust Scheduling with GFlowNets—0
Robust Visual Tracking via Statistical Positive Sample Generation and Gradient Aware Learning—0
Role Diversity Matters: A Study of Cooperative Training Strategies for Multi-Agent RL—0
Role of Structural and Conformational Diversity for Machine Learning Potentials—0
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