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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 6226–6250 of 9051 papers

TitleStatusHype
Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks—0
Why SOV might be initially preferred and then lost or recovered? A theoretical framework—0
Why the Mansfield Rule can't work: a supply demand analysis—0
Why You Should Try the Real Data for the Scene Text Recognition—0
Wide Aspect Ratio Matching for Robust Face Detection—0
Widely-distributed Radar Imaging Based on Consensus ADMM—0
Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search—0
WiderPerson: A Diverse Dataset for Dense Pedestrian Detection in the Wild—0
Widespread bursts of diversification in microbial phylogenies—0
Wiktionnaire's Wikicode GLAWIfied: a Workable French Machine-Readable Dictionary—0
Wills Aligner: Multi-Subject Collaborative Brain Visual Decoding—0
Channel Type Recognition in Wireless Communications: A Deep Learning Approach—0
Wireless Power Transfer with Distributed Antennas: System Design, Prototype, and Experiments—0
Wisdom from Diversity: Bias Mitigation Through Hybrid Human-LLM Crowds—0
Wisdom of Crowds cluster ensemble—0
Learning distinct features helps, provably—0
WoCE: a framework for clustering ensemble by exploiting the wisdom of Crowds theory—0
Words of Wisdom: Representational Harms in Learning From AI Communication—0
Workflow Complexity for Collaborative Interactions: Where are the Metrics? -- A Challenge—0
Workforce pDEI: Productivity Coupled with DEI—0
Workplace diversity and innovation performance: current state of affairs and future directions—0
World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions—0
WQT and DG-YOLO: towards domain generalization in underwater object detection—0
Writing as a testbed for open ended agents—0
XAGen: 3D Expressive Human Avatars Generation—0
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