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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 2701–2725 of 9051 papers

TitleStatusHype
AI-EDI-SPACE: A Co-designed Dataset for Evaluating the Quality of Public Spaces—0
DivNet: Diversity-Aware Self-Correcting Sequential Recommendation Networks—0
Federated Voxel Scene Graph for Intracranial HemorrhageCode0
Auditing Google's Search Algorithm: Measuring News Diversity Across Brazil, the UK, and the US—0
AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control—0
Clinical Evaluation of Medical Image Synthesis: A Case Study in Wireless Capsule Endoscopy—0
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms—0
What the %PCSA? Addressing Diversity in Lower-Limb Musculoskeletal Models: Age- and Sex-related Differences in PCSA and Muscle Mass—0
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKACode0
Teaching Embodied Reinforcement Learning Agents: Informativeness and Diversity of Language UseCode0
Machine learning models for Si nanoparticle growth in nonthermal plasma—0
Logistic Regression Analysis on the Dietary Behavior and the Risk of Nutritional Deficiency Dermatosis: The Case of Bicol Region, Philippines—0
Learning Video Representations without Natural Videos—0
A Universal Sets-level Optimization Framework for Next Set Recommendation—0
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling—0
Crowdsourcing Lexical Diversity—0
S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving—0
EMOTION: Expressive Motion Sequence Generation for Humanoid Robots with In-Context Learning—0
OpenSatMap: A Fine-grained High-resolution Satellite Dataset for Large-scale Map Construction—0
RIS-Aided Dual-Polarized MIMO: How Large a Surface is Needed to Beat Single Polarization?—0
The PV-ALE Dataset: Enhancing Apple Leaf Disease Classification Through Transfer Learning with Convolutional Neural Networks—0
FairSkin: Fair Diffusion for Skin Disease Image Generation—0
ReMix: Training Generalized Person Re-identification on a Mixture of Data—0
GRADE: Quantifying Sample Diversity in Text-to-Image Models—0
On the Role of Depth and Looping for In-Context Learning with Task Diversity—0
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