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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 3951–3975 of 9051 papers

TitleStatusHype
Non-Elitist Evolutionary Multi-Objective Optimisation: Proof-of-Principle Results—0
ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-TranslationCode0
Benchmarking state-of-the-art gradient boosting algorithms for classification—0
Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing—0
Diversify Your Vision Datasets with Automatic Diffusion-Based AugmentationCode1
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score DistillationCode1
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning—0
Mapping ChatGPT in Mainstream Media to Unravel Jobs and Diversity Challenges: Early Quantitative Insights through Sentiment Analysis and Word Frequency Analysis—0
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph DiffusionCode1
Optimized Custom Dataset for Efficient Detection of Underwater TrashCode1
Diversity-Aware Coherence Loss for Improving Neural Topic ModelsCode0
Unifying gradient regularization for Heterogeneous Graph Neural NetworksCode0
Rethinking Diversity in Deep Neural Network Testing—0
Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image SegmentationCode1
Learning to Act through Evolution of Neural Diversity in Random Neural Networks—0
Federated Learning Model Aggregation in Heterogenous Aerial and Space Networks—0
Manifold Diffusion Fields—0
Representation Online Matters: Practical End-to-End Diversification in Search and Recommender Systems—0
Balancing Effect of Training Dataset Distribution of Multiple Styles for Multi-Style Text Transfer—0
Psychological Metrics for Dialog System Evaluation—0
How Predictable Are Large Language Model Capabilities? A Case Study on BIG-benchCode0
Voices of Her: Analyzing Gender Differences in the AI Publication WorldCode0
Drafting Event Schemas using Language Models—0
Dolphin: A Challenging and Diverse Benchmark for Arabic NLG—0
Dior-CVAE: Pre-trained Language Models and Diffusion Priors for Variational Dialog GenerationCode0
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