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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 6201–6225 of 9051 papers

TitleStatusHype
On the Role of Depth and Looping for In-Context Learning with Task Diversity—0
On the Role of Edge Dependency in Graph Generative Models—0
On the Role of Receptive Field in Unsupervised Sim-to-Real Image Translation—0
On the Runtime Analysis of the Clearing Diversity-Preserving Mechanism—0
On the Scalability of Diffusion-based Text-to-Image Generation—0
On the Scalability of GNNs for Molecular Graphs—0
On the Statistical Complexity of Estimating VENDI Scores from Empirical Data—0
On the Structural Generalization in Text-to-SQL—0
On the Suitability of Representations for Quality Diversity Optimization of Shapes—0
On the Theory of Transfer Learning: The Importance of Task Diversity—0
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training—0
On the universality of cognitive tests—0
Understanding and Estimating Domain Complexity Across Domains—0
Understanding and Evaluating Hallucinations in 3D Visual Language Models—0
On the Use of Diversity Mechanisms in Dynamic Constrained Continuous Optimization—0
On the use of feature-maps and parameter control for improved quality-diversity meta-evolution—0
On the Use of Quality Diversity Algorithms for The Traveling Thief Problem—0
On time-consistent equilibrium stopping under aggregation of diverse discount rates—0
OOD Augmentation May Be at Odds with Open-Set Recognition—0
OOD-Speech: A Large Bengali Speech Recognition Dataset for Out-of-Distribution Benchmarking—0
Open Challenges in the Formal Verification of Autonomous Driving—0
OpenCodeReasoning: Advancing Data Distillation for Competitive Coding—0
OpenDance: Multimodal Controllable 3D Dance Generation Using Large-scale Internet Data—0
OpenDataLab: Empowering General Artificial Intelligence with Open Datasets—0
Understanding and Improving Source-free Domain Adaptation from a Theoretical Perspective—0
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