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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 6351–6375 of 9051 papers

TitleStatusHype
Who are the gatekeepers of economics? Geographic diversity, gender composition, and interlocking editorship of journal boards—0
Neuronal and structural differentiation in the emergence of abstract rules in hierarchically modulated spiking neural networks—0
Paraphrase Generation by Learning How to Edit from Samples—0
Understanding the Role of Functional Diversity in Weight-Ensembling with Ingredient Selection and Multidimensional Scaling—0
Are All Training Examples Created Equal? An Empirical Study—0
Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs—0
Parental Guidance: Efficient Lifelong Learning through Evolutionary Distillation—0
Parent Oriented Teacher Selection Causes Language Diversity—0
Understanding the Role of Temperature in Diverse Question Generation by GPT-4—0
PARIKSHA: A Large-Scale Investigation of Human-LLM Evaluator Agreement on Multilingual and Multi-Cultural Data—0
ParlamentParla: A Speech Corpus of Catalan Parliamentary Sessions—0
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning—0
Parsimonious Labeling—0
Parsing Occluded People—0
Part Discovery from Partial Correspondence—0
PartFormer: Awakening Latent Diverse Representation from Vision Transformer for Object Re-Identification—0
Partially Randomizing Transformer Weights for Dialogue Response Diversity—0
Partially Recentralization Softmax Loss for Vision-Language Models Robustness—0
Partial Off-Policy Learning: Balance Accuracy and Diversity for Human-Oriented Image Captioning—0
Understanding trade-offs in classifier bias with quality-diversity optimization: an application to talent management—0
Architext: Language-Driven Generative Architecture Design—0
Participatory Budgeting with Donations and Diversity Constraints—0
Participatory Design of AI with Children: Reflections on IDC Design Challenge—0
ARCH-Elites: Quality-Diversity for Urban Design—0
ArchCAD-400K: An Open Large-Scale Architectural CAD Dataset and New Baseline for Panoptic Symbol Spotting—0
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