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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 1526–1550 of 9051 papers

TitleStatusHype
Cross-Domain Feature Augmentation for Domain GeneralizationCode1
Approximating Gradients for Differentiable Quality Diversity in Reinforcement LearningCode1
Probabilistic Prompt Distribution Learning for Animal Pose EstimationCode1
Probabilistic Time Series Forecasting with Shape and Temporal DiversityCode1
Probabilistic Topic Modelling with Transformer RepresentationsCode1
CityPersons: A Diverse Dataset for Pedestrian DetectionCode1
Process-Supervised LLM Recommenders via Flow-guided TuningCode1
Profiling Pareto Front With Multi-Objective Stein Variational Gradient DescentCode1
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse LearningCode1
Automatically Generating Numerous Context-Driven SFT Data for LLMs across Diverse GranularityCode1
COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT ImagesCode1
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine LearningCode1
Class-Balancing Diffusion ModelsCode1
A Map of Diverse Synthetic Stable Roommates InstancesCode1
Covariance Matrix Adaptation for the Rapid Illumination of Behavior SpaceCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational ModelCode1
Automated segmentation and morphological characterization of placental histology images based on a single labeled imageCode1
Cooperative Open-ended Learning Framework for Zero-shot CoordinationCode1
QGFN: Controllable Greediness with Action ValuesCode1
Qimera: Data-free Quantization with Synthetic Boundary Supporting SamplesCode1
Quality Controlled Paraphrase GenerationCode1
Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features CriticsCode1
Quality-Diversity Generative Sampling for Learning with Synthetic DataCode1
Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata EcosystemsCode1
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