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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 3851–3875 of 9051 papers

TitleStatusHype
Personalized Elastic Embedding Learning for On-Device Recommendation—0
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text GenerationCode0
FALL-E: A Foley Sound Synthesis Model and StrategiesCode1
Understanding Deep Generative Models with Generalized Empirical LikelihoodsCode1
Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High DimensionsCode0
Differentiable Instruction Optimization for Cross-Task GeneralizationCode0
On Evolvability and Behavior Landscapes in Neuroevolutionary Divergent Search—0
Taming Diffusion Models for Music-driven Conducting Motion GenerationCode1
Domain-specific ChatBots for Science using EmbeddingsCode1
The Core & Periphery Hypothesis: A Conceptual Basis for Generality in Cell and Developmental Biology—0
A9 Intersection Dataset: All You Need for Urban 3D Camera-LiDAR Roadside Perception—0
Text Promptable Surgical Instrument Segmentation with Vision-Language ModelsCode1
BRUDEX Database: Binaural Room Impulse Responses with Uniformly Distributed External Microphones—0
DiffuDetox: A Mixed Diffusion Model for Text Detoxification—0
Data Augmentation for Seizure Prediction with Generative Diffusion Model—0
Learning to Specialize: Joint Gating-Expert Training for Adaptive MoEs in Decentralized Settings—0
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative ModelsCode1
Curatr: A Platform for Semantic Analysis and Curation of Historical Literary Texts—0
MolCAP: Molecular Chemical reActivity pretraining and prompted-finetuning enhanced molecular representation learning—0
Deep Learning-Enabled Zero-Touch Device Identification: Mitigating the Impact of Channel Variability Through MIMO Diversity—0
Parameter-efficient Dysarthric Speech Recognition Using Adapter Fusion and Householder Transformation—0
Augmenting Zero-Shot Detection Training with Image Labels—0
Generating Language Corrections for Teaching Physical Control TasksCode0
Feature Fusion from Head to Tail for Long-Tailed Visual RecognitionCode1
AROID: Improving Adversarial Robustness Through Online Instance-Wise Data AugmentationCode0
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