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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 2951–2975 of 9051 papers

TitleStatusHype
Deconditional Downscaling with Gaussian ProcessesCode0
Expanding functional protein sequence space using generative adversarial networksCode0
Does In-Context Learning Really Learn? Rethinking How Large Language Models Respond and Solve Tasks via In-Context LearningCode0
Exhaustive Exploitation of Nature-inspired Computation for Cancer Screening in an Ensemble MannerCode0
Expanding, Retrieving and Infilling: Diversifying Cross-Domain Question Generation with Flexible TemplatesCode0
Decomposed Distribution Matching in Dataset CondensationCode0
Challenges of Generating Structurally Diverse GraphsCode0
Dynamic Quality-Diversity SearchCode0
Evolvability ES: Scalable and Direct Optimization of EvolvabilityCode0
Decoding MIE: A Novel Dataset Approach Using Topic Extraction and Affiliation ParsingCode0
Evolution of a Functionally Diverse Swarm via a Novel Decentralised Quality-Diversity AlgorithmCode0
Guardian of the Ensembles: Introducing Pairwise Adversarially Robust Loss for Resisting Adversarial Attacks in DNN EnsemblesCode0
Exact Fusion via Feature Distribution Matching for Few-shot Image GenerationCode0
Dynamics of niche construction in adaptable populations evolving in diverse environmentsCode0
A variational selection mechanism for article comment generationCode0
Evolutionary bagging for ensemble learningCode0
Evolutionary Generative Adversarial NetworksCode0
EventDrop: data augmentation for event-based learningCode0
DynED: Dynamic Ensemble Diversification in Data Stream ClassificationCode0
DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal GraphsCode0
PECAN: Leveraging Policy Ensemble for Context-Aware Zero-Shot Human-AI CoordinationCode0
Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule GenerationCode0
Event Transition Planning for Open-ended Text GenerationCode0
Accelerating Prototype-Based Drug Discovery using Conditional Diversity NetworksCode0
Evaluator for Emotionally Consistent ChatbotsCode0
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