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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 7076–7100 of 9051 papers

TitleStatusHype
NightCC: Nighttime Color Constancy via Adaptive Channel Masking—0
Nitrogen-induced hysteresis in grassland biodiversity: a theoretical test of litter-mediated mechanisms—0
Language Varieties of Italy: Technology Challenges and Opportunities—0
No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World—0
NOD-TAMP: Generalizable Long-Horizon Planning with Neural Object Descriptors—0
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models—0
Noise Consistency Regularization for Improved Subject-Driven Image Synthesis—0
Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning—0
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization—0
NOMA Computation Over Multi-Access Channels for Multimodal Sensing—0
NOMA Visible Light Communication System with Angle Diversity Receivers—0
Non-Centralized Navigation for Source Localization by Cooperative UAVs—0
Non-Coherent MIMO-OFDM Uplink empowered by the Spatial Diversity in Reflecting Surfaces—0
Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results—0
Nonisotropic Gaussian Diffusion for Realistic 3D Human Motion Prediction—0
Non-Linear Flow Matching for Full-Atom Peptide Design—0
Nonlinearity Characteristic of High Impedance Fault at Resonant Distribution Networks: Theoretical Basis to Identify the Faulty Feeder—0
Non-local Policy Optimization via Diversity-regularized Collaborative Exploration—0
No NLP Task Should be an Island: Multi-disciplinarity for Diversity in News Recommender Systems—0
Non-monotone Sequential Submodular Maximization—0
Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery—0
Non-Orthogonal Multiple Access in the Presence of Additive Generalized Gaussian Noise—0
Non-Orthogonal Multiple Access (NOMA) With Multiple Intelligent Reflecting Surfaces—0
Non-Parallel Voice Conversion for ASR Augmentation—0
Non-rigid 3D shape retrieval based on multi-view metric learning—0
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