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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 8551–8575 of 9051 papers

TitleStatusHype
SSCL-IDS: Enhancing Generalization of Intrusion Detection with Self-Supervised Contrastive LearningCode0
Multi-Frequency Channel Modeling for Millimeter Wave and THz Wireless Communication via Generative Adversarial NetworksCode0
Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality SelectionCode0
Few-shot Quality-Diversity OptimizationCode0
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image SegmentationCode0
The Price of Format: Diversity Collapse in LLMsCode0
A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial DiversityCode0
A variational selection mechanism for article comment generationCode0
Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule GenerationCode0
S-SYNTH: Knowledge-Based, Synthetic Generation of Skin ImagesCode0
Multi-Label Bayesian Active Learning with Inter-Label RelationshipsCode0
A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural NetworksCode0
Few-shot Personalization of LLMs with Mis-aligned ResponsesCode0
AILS-NTUA at SemEval-2025 Task 8: Language-to-Code prompting and Error Fixing for Tabular Question AnsweringCode0
The Proper Care and Feeding of CAMELS: How Limited Training Data Affects Streamflow PredictionCode0
Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and CostCode0
Multilingual Detection of Personal Employment Status on TwitterCode0
Stacked Ensemble Machine Learning for Range-Separation ParametersCode0
Few-shot Image Generation with Diffusion ModelsCode0
Multilingual Lexical Simplification via Paraphrase GenerationCode0
Multilingual Neural Machine Translation with Knowledge DistillationCode0
Video-based Cross-modal Auxiliary Network for Multimodal Sentiment AnalysisCode0
Class Incremental Learning with Multi-Teacher DistillationCode0
Multilingual State Space Models for Structured Question Answering in Indic LanguagesCode0
CircleGAN: Generative Adversarial Learning across Spherical CirclesCode0
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