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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 2526–2550 of 9051 papers

TitleStatusHype
AnyHome: Open-Vocabulary Generation of Structured and Textured 3D Homes—0
A Comprehensive Survey of Time Series Forecasting: Architectural Diversity and Open Challenges—0
CFTS-GAN: Continual Few-Shot Teacher Student for Generative Adversarial Networks—0
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds—0
AnyFace: Free-style Text-to-Face Synthesis and Manipulation—0
CFILT IIT Bombay@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion using Multilingual Representation fromTransformers—0
AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea—0
Domain Randomization via Entropy Maximization—0
CET2: Modelling Topic Transitions for Coherent and Engaging Knowledge-Grounded Conversations—0
An upper bound of the mutation probability in the genetic algorithm for general 0-1 knapsack problem—0
An Unsupervised Semantic Sentence Ranking Scheme for Text Documents—0
Adversarial optimization leads to over-optimistic security-constrained dispatch, but sampling can help—0
An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio—0
CDL: Curriculum Dual Learning for Emotion-Controllable Response Generation—0
Deep Single Image Deraining using An Asymetric Cycle Generative and Adversarial Framework—0
A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications—0
7 Tesla multimodal MRI dataset of ex-vivo human brain—0
CCVA-FL: Cross-Client Variations Adaptive Federated Learning for Medical Imaging—0
An Unscented Kalman Filter-Informed Neural Network for Vehicle Sideslip Angle Estimation—0
CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation—0
CAViaR: Context Aware Video Recommendations—0
A Comprehensive Review of Data-Driven Co-Speech Gesture Generation—0
Cause-Aware Empathetic Response Generation via Chain-of-Thought Fine-Tuning—0
Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering—0
Antithetic Noise in Diffusion Models—0
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