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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 2626–2650 of 9051 papers

TitleStatusHype
Exploring Non-Linear Effects of Built Environment on Travel Using an Integrated Machine Learning and Inferential Modeling Approach: A Three-Wave Repeated Cross-Sectional Study—0
Controlling Diversity at Inference: Guiding Diffusion Recommender Models with Targeted Category PreferencesCode0
Causal Effect of Group Diversity on Redundancy and Coverage in Peer-Reviewing—0
Higher Order Graph Attention Probabilistic Walk Networks—0
The ADUULM-360 Dataset -- A Multi-Modal Dataset for Depth Estimation in Adverse WeatherCode0
Retinal Vessel Segmentation via Neuron Programming—0
ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling—0
F^3OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics—0
Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network—0
Melanoma Detection with Uncertainty Quantification—0
Large Language Models as User-Agents for Evaluating Task-Oriented-Dialogue Systems—0
Affine Frequency Division Multiplexing with Index Modulation: Full Diversity Condition, Performance Analysis, and Low-Complexity Detection—0
The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning—0
Being Considerate as a Pathway Towards Pluralistic Alignment for Agentic AI—0
Entropy and type-token ratio in gigaword corpora—0
Iterative Batch Reinforcement Learning via Safe Diversified Model-based Policy Search—0
Adaptively Augmented Consistency Learning: A Semi-supervised Segmentation Framework for Remote Sensing—0
CorrSynth -- A Correlated Sampling Method for Diverse Dataset Generation from LLMs—0
Graph Neural Network Generalization with Gaussian Mixture Model Based Augmentation—0
Quantity versus Diversity: Influence of Data on Detecting EEG Pathology with Advanced ML Models—0
Multi-Perspective Stance DetectionCode0
PerceiverS: A Multi-Scale Perceiver with Effective Segmentation for Long-Term Expressive Symbolic Music Generation—0
Integrating Chaotic Evolutionary and Local Search Techniques in Decision Space for Enhanced Evolutionary Multi-Objective Optimization—0
Mix from Failure: Confusion-Pairing Mixup for Long-Tailed Recognition—0
Fair Summarization: Bridging Quality and Diversity in Extractive SummariesCode0
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