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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 1251–1275 of 9051 papers

TitleStatusHype
Axiomatic Explainer Globalness via Optimal Transport—0
PRIMO: Progressive Induction for Multi-hop Open Rule Generation—0
Designing a Robust Radiology Report Generation System—0
Role Play: Learning Adaptive Role-Specific Strategies in Multi-Agent Interactions—0
The Role of Domain Randomization in Training Diffusion Policies for Whole-Body Humanoid Control—0
DivNet: Diversity-Aware Self-Correcting Sequential Recommendation Networks—0
α-TCVAE: On the relationship between Disentanglement and Diversity—0
AI-EDI-SPACE: A Co-designed Dataset for Evaluating the Quality of Public Spaces—0
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language ModelsCode0
Federated Voxel Scene Graph for Intracranial HemorrhageCode0
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
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
Clinical Evaluation of Medical Image Synthesis: A Case Study in Wireless Capsule Endoscopy—0
AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control—0
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms—0
GS-Blur: A 3D Scene-Based Dataset for Realistic Image DeblurringCode1
Auditing Google's Search Algorithm: Measuring News Diversity Across Brazil, the UK, and the US—0
Teaching Embodied Reinforcement Learning Agents: Informativeness and Diversity of Language UseCode0
Learning Video Representations without Natural Videos—0
EgoMimic: Scaling Imitation Learning via Egocentric VideoCode2
RIS-Aided Dual-Polarized MIMO: How Large a Surface is Needed to Beat Single Polarization?—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
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