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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 3676–3700 of 9051 papers

TitleStatusHype
Neural Categorical Priors for Physics-Based Character Control—0
Compositional Feature Augmentation for Unbiased Scene Graph GenerationCode1
Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection—0
ZYN: Zero-Shot Reward Models with Yes-No Questions for RLAIFCode1
Controlling Character Motions without Observable Driving Source—0
DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic DiversityCode1
Quality Diversity under Sparse Reward and Sparse Interaction: Application to Grasping in RoboticsCode1
Composable Core-sets for Diversity Approximation on Multi-Dataset Streams—0
Fine-grained building roof instance segmentation based on domain adapted pretraining and composite dual-backbone—0
Evaluating the diversity and utility of materials proposed by generative models—0
Analyzing and controlling diversity in quantum-behaved particle swarm optimization—0
Cross-view Semantic Alignment for Livestreaming Product RecognitionCode0
Multimodal Color Recommendation in Vector Graphic Documents—0
Social Media, Topic Modeling and Sentiment Analysis in Municipal Decision Support—0
A Comparative Study of Image-to-Image Translation Using GANs for Synthetic Child Race Data—0
Path Signatures for Diversity in Probabilistic Trajectory Optimisation—0
Implicit neural representations for joint decomposition and registration of gene expression images in the marmoset brainCode0
From Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain RemovalCode1
Measuring Variety, Balance, and Disparity: An Analysis of Media Coverage of the 2021 German Federal Election—0
QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration—0
FireFly A Synthetic Dataset for Ember Detection in WildfireCode0
Towards Multiple References Era -- Addressing Data Leakage and Limited Reference Diversity in NLG EvaluationCode0
Auditing and Robustifying COVID-19 Misinformation Datasets via Anticontent Sampling—0
Self-Distillation Prototypes Network: Learning Robust Speaker Representations without Supervision—0
Redundancy Aware Multi-Reference Based Gainwise Evaluation of Extractive Summarization—0
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