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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 1201–1225 of 9051 papers

TitleStatusHype
Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable DiffusionCode1
End-to-End Optimization of Scene LayoutCode1
Controllable Text Generation via Probability Density Estimation in the Latent SpaceCode1
Controllable Open-ended Question Generation with A New Question Type OntologyCode1
Controllable Video Captioning with an Exemplar SentenceCode1
Enhancing Diversity in Teacher-Student Networks via Asymmetric branches for Unsupervised Person Re-identificationCode1
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial DefenseCode1
Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity RecognitionCode1
EnvEdit: Environment Editing for Vision-and-Language NavigationCode1
EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text ClassificationCode1
Cooperative Open-ended Learning Framework for Zero-shot CoordinationCode1
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse LearningCode1
Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code ContributionsCode1
Evaluating the Evaluation of Diversity in Natural Language GenerationCode1
Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text GenerationCode1
Contrastive Syn-to-Real GeneralizationCode1
An Empirical Investigation of Pre-Trained Transformer Language Models for Open-Domain Dialogue GenerationCode1
Explain Me the Painting: Multi-Topic Knowledgeable Art Description GenerationCode1
Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active ExplorationCode1
Exploring Design of Multi-Agent LLM Dialogues for Research IdeationCode1
Beyond Performance Plateaus: A Comprehensive Study on Scalability in Speech EnhancementCode1
Exploring Empty Spaces: Human-in-the-Loop Data AugmentationCode1
Controllable and Guided Face Synthesis for Unconstrained Face RecognitionCode1
Contrastive Model Inversion for Data-Free Knowledge DistillationCode1
AMPED: Adaptive Multi-objective Projection for balancing Exploration and skill DiversificationCode1
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