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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 3701–3725 of 9051 papers

TitleStatusHype
Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning—0
Fill In The Gaps: Model Calibration and Generalization with Synthetic Data—0
Filter-based Discriminative Autoencoders for Children Speech Recognition—0
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns—0
Diverse Prompts: Illuminating the Prompt Space of Large Language Models with MAP-Elites—0
Find and Focus: Retrieve and Localize Video Events with Natural Language Queries—0
Angle Sensitive Pixels for Lensless Imaging on Spherical Sensors—0
Diverse Projection Ensembles for Distributional Reinforcement Learning—0
Finding Near-Optimal Portfolios With Quality-Diversity—0
Finding Pragmatic Differences Between Disciplines—0
ADLM -- stega: A Universal Adaptive Token Selection Algorithm for Improving Steganographic Text Quality via Information Entropy—0
Generating Diverse Training Samples for Relation Extraction with Large Language Models—0
Generating Diverse Translation with Perturbed kNN-MT—0
Finding Support Examples for In-Context Learning—0
Fine-grained Activities of People Worldwide—0
Fine-grained building roof instance segmentation based on domain adapted pretraining and composite dual-backbone—0
Controlling Character Motions without Observable Driving Source—0
Diverse Priors for Deep Reinforcement Learning—0
Angle Diversity Trasmitter For High Speed Data Center Uplink Communications—0
Fine-grained Semantic Constraint in Image Synthesis—0
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density—0
Fine-Grained Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation—0
3D-LDM: Neural Implicit 3D Shape Generation with Latent Diffusion Models—0
Generating Diverse Realistic Laughter for Interactive Art—0
Angle diversity receiver as a key enabler for reliable ORIS-based Visible Light Communication—0
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