SOTAVerified

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

Showing 21512175 of 9051 papers

TitleStatusHype
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?Code0
IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-trainingCode0
ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model RobustnessCode0
Hierarchical Reinforcement Learning via Advantage-Weighted Information MaximizationCode0
ChatGPT as a commenter to the news: can LLMs generate human-like opinions?Code0
CHARMS: A Cognitive Hierarchical Agent for Reasoning and Motion Stylization in Autonomous DrivingCode0
Hierarchical Federated Learning in Multi-hop Cluster-Based VANETsCode0
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic SystemsCode0
Hierarchical Pruning of Deep Ensembles with Focal DiversityCode0
Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail RecognitionCode0
A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger designCode0
Harnessing Distribution Ratio Estimators for Learning Agents with Quality and DiversityCode0
GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trickCode0
Adversarial Transformation Networks: Learning to Generate Adversarial ExamplesCode0
Guylingo: The Republic of Guyana Creole CorporaCode0
Harmony in Diversity: Merging Neural Networks with Canonical Correlation AnalysisCode0
Heterogeneous Random ForestCode0
High-dimensional Assisted Generative Model for Color Image RestorationCode0
Growing Artificial Neural Networks for Control: the Role of Neuronal DiversityCode0
A Patch-Based Algorithm for Diverse and High Fidelity Single Image GenerationCode0
Channel Augmented Joint Learning for Visible-Infrared RecognitionCode0
Grouping Words with Semantic DiversityCode0
Group Relative Policy Optimization for Image CaptioningCode0
Guiding and Diversifying LLM-Based Story Generation via Answer Set ProgrammingCode0
Challenges of Generating Structurally Diverse GraphsCode0
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