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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 87518775 of 9051 papers

TitleStatusHype
Diffusion Models for Probabilistic Deconvolution of Galaxy ImagesCode0
Diversifying Neural Text Generation with Part-of-Speech Guided Softmax and SamplingCode0
Structurally Diverse Sampling for Sample-Efficient Training and Comprehensive EvaluationCode0
Structured and Informed Probabilistic Modeling with the Thermodynamic Kolmogorov-Arnold ModelCode0
A Hierarchical Deep Learning Approach for Minority Instrument DetectionCode0
Exploring the Role of Diversity in Example Selection for In-Context LearningCode0
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data AugmentationCode0
Exploring the Performance-Reproducibility Trade-off in Quality-DiversityCode0
Exploring the Evolution of GANs through Quality DiversityCode0
Discovering Representations for Black-box OptimizationCode0
Structured Ensembles: an Approach to Reduce the Memory Footprint of Ensemble MethodsCode0
A Neural Compositional Paradigm for Image CaptioningCode0
Exploring weight initialization, diversity of solutions, and degradation in recurrent neural networks trained for temporal and decision-making tasksCode0
Response Generation by Context-aware Prototype EditingCode0
Exploring the Capabilities of Large Language Models for Generating Diverse Design SolutionsCode0
CAT: Contrastive Adapter Training for Personalized Image GenerationCode0
Response to comment on Mutualism weaken the latitudinal diversity gradient among oceanic islandsCode0
New Datasets and a Benchmark of Document Network Embedding Methods for Scientific Expert FindingCode0
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?Code0
DiffuCOMET: Contextual Commonsense Knowledge DiffusionCode0
New Metrics to Encourage Innovation and Diversity in Information Retrieval ApproachesCode0
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive StrategiesCode0
Automatic Synthesis of Diverse Weak Supervision Sources for Behavior AnalysisCode0
Result Diversification by Multi-objective Evolutionary Algorithms with Theoretical GuaranteesCode0
Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson ProblemCode0
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