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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 351–375 of 9051 papers

TitleStatusHype
Measuring Diversity in Synthetic DatasetsCode1
Jakiro: Boosting Speculative Decoding with Decoupled Multi-Head via MoECode1
Trajectory World Models for Heterogeneous EnvironmentsCode1
RIGNO: A Graph-based framework for robust and accurate operator learning for PDEs on arbitrary domainsCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
WanJuanSiLu: A High-Quality Open-Source Webtext Dataset for Low-Resource LanguagesCode1
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series ForecastingCode1
Curiosity-Driven Reinforcement Learning from Human FeedbackCode1
Evaluation and Efficiency Comparison of Evolutionary Algorithms for Service Placement Optimization in Fog ArchitecturesCode1
DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI ReconstructionCode1
Toward Intelligent and Secure Cloud: Large Language Model Empowered Proactive DefenseCode1
A Large-Scale Study on Video Action Dataset CondensationCode1
No Preference Left Behind: Group Distributional Preference OptimizationCode1
Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration PathCode1
Optimal signal transmission and timescale diversity in a model of human brain operating near criticalityCode1
HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMsCode1
Hybrid CNN-LSTM based Indoor Pedestrian Localization with CSI Fingerprint MapsCode1
StrandHead: Text to Strand-Disentangled 3D Head Avatars Using Hair Geometric PriorsCode1
Relation-Guided Adversarial Learning for Data-free Knowledge TransferCode1
Exploring Semantic Consistency and Style Diversity for Domain Generalized Semantic SegmentationCode1
Augmenting Sequential Recommendation with Balanced Relevance and DiversityCode1
HyperMARL: Adaptive Hypernetworks for Multi-Agent RLCode1
U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMsCode1
Interpreting single-cell and spatial omics data using deep neural network training dynamicsCode1
Towards Rich Emotions in 3D Avatars: A Text-to-3D Avatar Generation BenchmarkCode1
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