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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

Showing 30263050 of 9051 papers

TitleStatusHype
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding DatasetsCode0
Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape AnalysisCode0
Dataset Clustering for Improved Offline Policy LearningCode0
Evolutionary bagging for ensemble learningCode0
ExplainCPE: A Free-text Explanation Benchmark of Chinese Pharmacist ExaminationCode0
Exploring Precision and Recall to assess the quality and diversity of LLMsCode0
Discovering Representations for Black-box OptimizationCode0
Evaluating Neural Language Models as Cognitive Models of Language AcquisitionCode0
Dataset and Benchmark for Urdu Natural Scenes Text Detection, Recognition and Visual Question AnsweringCode0
Evaluating Diversity in Automatic Poetry GenerationCode0
Evaluating Fairness in Argument RetrievalCode0
Evaluating and Improving Graph to Text Generation with Large Language ModelsCode0
Automatic Synthesis of Diverse Weak Supervision Sources for Behavior AnalysisCode0
Evaluating Coherence in Dialogue Systems using EntailmentCode0
Pruning Techniques for Mixed Ensembles of Genetic Programming ModelsCode0
Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating AttentionCode0
AMLNet: Adversarial Mutual Learning Neural Network for Non-AutoRegressive Multi-Horizon Time Series ForecastingCode0
Evaluating Creative Short Story Generation in Humans and Large Language ModelsCode0
ETS: Efficient Tree Search for Inference-Time ScalingCode0
Ethical Considerations for Responsible Data CurationCode0
EuLearn: A 3D database for learning Euler characteristicsCode0
Establishing a Unified Evaluation Framework for Human Motion Generation: A Comparative Analysis of MetricsCode0
A mirror-Unet architecture for PET/CT lesion segmentationCode0
ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials DataCode0
Data Fusion for Deep Learning on Transport Mode Detection: A Case StudyCode0
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