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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 526550 of 9051 papers

TitleStatusHype
G-DIG: Towards Gradient-based Diverse and High-quality Instruction Data Selection for Machine TranslationCode1
Goals as Reward-Producing ProgramsCode1
PT43D: A Probabilistic Transformer for Generating 3D Shapes from Single Highly-Ambiguous RGB ImagesCode1
SynthesizRR: Generating Diverse Datasets with Retrieval AugmentationCode1
Color Space Learning for Cross-Color Person Re-IdentificationCode1
Cross-Domain Feature Augmentation for Domain GeneralizationCode1
Treatment Effect Estimation for User Interest Exploration on Recommender SystemsCode1
TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable PromptCode1
BenthicNet: A global compilation of seafloor images for deep learning applicationsCode1
Pedestrian Attribute Recognition as Label-balanced Multi-label LearningCode1
Navigating Chemical Space with Latent FlowsCode1
Towards Geographic Inclusion in the Evaluation of Text-to-Image ModelsCode1
Argumentative Large Language Models for Explainable and Contestable Claim VerificationCode1
Inherent Trade-Offs between Diversity and Stability in Multi-Task BenchmarksCode1
KVP10k : A Comprehensive Dataset for Key-Value Pair Extraction in Business DocumentsCode1
SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for RecommendationCode1
Modeling Caption Diversity in Contrastive Vision-Language PretrainingCode1
Soft Prompt Generation for Domain GeneralizationCode1
CompilerDream: Learning a Compiler World Model for General Code OptimizationCode1
Elucidating the Design Space of Dataset CondensationCode1
FineRec:Exploring Fine-grained Sequential RecommendationCode1
MambaPupil: Bidirectional Selective Recurrent model for Event-based Eye trackingCode1
Forcing Diffuse Distributions out of Language ModelsCode1
Memory Sharing for Large Language Model based AgentsCode1
How Consistent are Clinicians? Evaluating the Predictability of Sepsis Disease Progression with Dynamics ModelsCode1
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