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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 2551–2575 of 9051 papers

TitleStatusHype
Benchmarking the Fairness of Image Upsampling MethodsCode0
Dialogue Quality and Emotion Annotations for Customer Support ConversationsCode0
Frequency Tracking Features for Data-Efficient Deep Siren IdentificationCode0
From Distributional to Overton Pluralism: Investigating Large Language Model AlignmentCode0
Fully Automatic Video Colorization with Self-Regularization and DiversityCode0
DialogueAgents: A Hybrid Agent-Based Speech Synthesis Framework for Multi-Party DialogueCode0
Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple ExpertsCode0
Improving Contextualized Topic Models with Negative SamplingCode0
Foundation Models at Work: Fine-Tuning for Fairness in Algorithmic HiringCode0
Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target ImputationCode0
DI2: prior-free and multi-item discretization ofbiomedical data and its applicationsCode0
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through OptionsCode0
dhSegment: A generic deep-learning approach for document segmentationCode0
DGSAN: Discrete Generative Self-Adversarial NetworkCode0
Benchmarking Linguistic Diversity of Large Language ModelsCode0
Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-TuningCode0
Benchmarking Large Language Model Uncertainty for Prompt OptimizationCode0
FuncGenFoil: Airfoil Generation and Editing Model in Function SpaceCode0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-TranslationCode0
Adder Attention for Vision TransformerCode0
Flickr-PAD: New Face High-Resolution Presentation Attack Detection DatabaseCode0
Benchmarking histopathology foundation models in a multi-center dataset for skin cancer subtypingCode0
A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddingsCode0
Flexible Modeling of Diversity with Strongly Log-Concave DistributionsCode0
DFPE: A Diverse Fingerprint Ensemble for Enhancing LLM PerformanceCode0
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