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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 2726–2750 of 9051 papers

TitleStatusHype
GRADE: Quantifying Sample Diversity in Text-to-Image Models—0
BENCHAGENTS: Automated Benchmark Creation with Agent Interaction—0
On the Role of Depth and Looping for In-Context Learning with Task Diversity—0
Current State-of-the-Art of Bias Detection and Mitigation in Machine Translation for African and European Languages: a Review—0
Exploring the Design Space of Diffusion Bridge Models via Stochasticity Control—0
Semantic Component Analysis: Discovering Patterns in Short Texts Beyond TopicsCode0
Can Users Detect Biases or Factual Errors in Generated Responses in Conversational Information-Seeking?Code0
ADLM -- stega: A Universal Adaptive Token Selection Algorithm for Improving Steganographic Text Quality via Information Entropy—0
Reducing the Scope of Language Models—0
Neural Network-Enhanced Disease Spread Dynamics Over Time and Space—0
Efficient Diversity-based Experience Replay for Deep Reinforcement Learning—0
Hierarchical Multiple Kernel K-Means Algorithm Based on Sparse Connectivity—0
CLOUDSPAM: Contrastive Learning On Unlabeled Data for Segmentation and Pre-Training Using Aggregated Point Clouds and MoCoCode0
GFlowNet Fine-tuning for Diverse Correct Solutions in Mathematical Reasoning Tasks—0
Deep Concept Identification for Generative Design—0
Optimizing Keyphrase Ranking for Relevance and Diversity Using Submodular Function Optimization (SFO)Code0
Adversarial Environment Design via Regret-Guided Diffusion Models—0
Disentangling Genotype and Environment Specific Latent Features for Improved Trait Prediction using a Compositional Autoencoder—0
How high dimensional neural dynamics are confined in phase space—0
Multi-modal Motion Prediction using Temporal Ensembling with Learning-based Aggregation—0
Spatioformer: A Geo-encoded Transformer for Large-Scale Plant Species Richness Prediction—0
Improving Inverse Folding for Peptide Design with Diversity-regularized Direct Preference Optimization—0
Semi-supervised Chinese Poem-to-Painting Generation via Cycle-consistent Adversarial NetworksCode0
Creating and Repairing Robot Programs in Open-World Domains—0
Comparative Analysis of Indicators for Multiobjective Diversity Optimization—0
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