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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 2426–2450 of 9051 papers

TitleStatusHype
Generating Diverse and Meaningful CaptionsCode0
Beyond Factual Accuracy: Evaluating Coverage of Diverse Factual Information in Long-form Text GenerationCode0
Toward Improving Coherence and Diversity of Slogan GenerationCode0
Generating Diverse Descriptions from Semantic GraphsCode0
Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language ModelingCode0
Problematic Tokens: Tokenizer Bias in Large Language ModelsCode0
Generalized Face Anti-spoofing via Finer Domain Partition and Disentangling Liveness-irrelevant FactorsCode0
Generalized Dice Focal Loss trained 3D Residual UNet for Automated Lesion Segmentation in Whole-Body FDG PET/CT ImagesCode0
Beyond Digital "Echo Chambers": The Role of Viewpoint Diversity in Political DiscussionCode0
Diffusion Models for Probabilistic Deconvolution of Galaxy ImagesCode0
Generating Diverse and Accurate Visual Captions by Comparative Adversarial LearningCode0
A Deep Generative Artificial Intelligence system to decipher species coexistence patternsCode0
Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data LimitationsCode0
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?Code0
GAIT: A Geometric Approach to Information TheoryCode0
Generating Informative and Diverse Conversational Responses via Adversarial Information MaximizationCode0
Generating Language Corrections for Teaching Physical Control TasksCode0
GDPP: Learning Diverse Generations Using Determinantal Point ProcessCode0
GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language UnderstandingCode0
Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer SatisfactionCode0
DimonGen: Diversified Generative Commonsense Reasoning for Explaining Concept RelationshipsCode0
GAN-GA: A Generative Model based on Genetic Algorithm for Medical Image GenerationCode0
Game Theory for Adversarial Attacks and DefensesCode0
"Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?Code0
An Electoral Approach to Diversify LLM-based Multi-Agent Collective Decision-MakingCode0
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