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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 7276–7300 of 9051 papers

TitleStatusHype
Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data AugmentationCode1
Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases—0
Person Re-Identification via Active Hard Sample Mining—0
Orthogonal Over-Parameterized TrainingCode1
Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline GenerationCode1
Understanding Knowledge Gaps in Visual Question Answering: Implications for Gap Identification and Testing—0
TextGAIL: Generative Adversarial Imitation Learning for Text Generation—0
Data Dieting in GAN Training—0
Improving the Robustness of QA Models to Challenge Sets with Variational Question-Answer Pair GenerationCode0
Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation—0
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
SNR-Based Features and Diverse Training Data for Robust DNN-Based Speech Enhancement—0
New Datasets and a Benchmark of Document Network Embedding Methods for Scientific Expert FindingCode0
Trying AGAIN instead of Trying Longer: Prior Learning for Automatic Curriculum Learning—0
Beer Organoleptic Optimisation: Utilising Swarm Intelligence and Evolutionary Computation MethodsCode0
Evaluating the Evaluation of Diversity in Natural Language GenerationCode1
Sparse Text GenerationCode1
The World is Not Binary: Learning to Rank with Grayscale Data for Dialogue Response Selection—0
Syntax-driven Iterative Expansion Language Models for Controllable Text Generation—0
Characterizing Halloumi cheese bacterial communities through metagenomic analysis—0
Finding Black Cat in a Coal Cellar -- Keyphrase Extraction & Keyphrase-Rubric Relationship Classification from Complex AssignmentsCode0
Consistent Multiple Sequence Decoding—0
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness—0
M2m: Imbalanced Classification via Major-to-minor TranslationCode1
Leveraging User-Diversity in Energy-Efficient Edge-Facilitated Collaborative Fog Computing—0
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