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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 6176–6200 of 9051 papers

TitleStatusHype
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer—0
On-the-Fly Feature Based Rapid Speaker Adaptation for Dysarthric and Elderly Speech Recognition—0
On the Generalization Error Bounds of Neural Networks under Diversity-Inducing Mutual Angular Regularization—0
On the Generation of Medical Question-Answer Pairs—0
On the ideas of the origin of eukaryotes: a critical review—0
On the Impact of Cross-Domain Data on German Language Models—0
Uncovering Semantics and Topics Utilized by Threat Actors to Deliver Malicious Attachments and URLs—0
On the Importance of Data Size in Probing Fine-tuned Models—0
Fast uncovering of protein sequence diversity from structure—0
On the Importance of Diversity in Question Generation for QA—0
On the Importance of Diversity in Re-Sampling for Imbalanced Data and Rare Events in Mortality Risk Models—0
On The Ingredients of an Effective Zero-shot Semantic Parser—0
On the Limitations of Model Stealing with Uncertainty Quantification Models—0
On the Linear Ordering Problem and the Rankability of Data—0
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off—0
On the Modeling Capabilities of Large Language Models for Sequential Decision Making—0
On the number of equilibria of the replicator-mutator dynamics for noisy social dilemmas—0
On the Performance of Non-Orthogonal Multiple Access Systems with Imperfect Successive Interference Cancellation—0
On the Performance of Pinching-Antenna Systems (PASS) with Orthogonal and Non-Orthogonal Multiple Access—0
On the Performance of UAV Relaying with Reconfigurable Antenna and Media Based Modulation in the Presence of Shadowed Fading—0
On the potential for open-endedness in neural networks—0
On the Power of Decision Trees in Auto-Regressive Language Modeling—0
On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text Generation—0
On the Robustness of Active Learning—0
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity—0
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