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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 4676–4700 of 9051 papers

TitleStatusHype
Item-based Variational Auto-encoder for Fair Music RecommendationCode1
The Robustness Limits of SoTA Vision Models to Natural Variation—0
LANS: Large-scale Arabic News Summarization Corpus—0
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain DomainsCode0
Multi-Objective GFlowNetsCode1
Batch Multi-Fidelity Active Learning with Budget Constraints—0
Learning General World Models in a Handful of Reward-Free Deployments—0
PoKE: Prior Knowledge Enhanced Emotional Support Conversation with Latent Variable—0
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation—0
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES—0
Diversity-Promoting Ensemble for Medical Image Segmentation—0
There Is No Standard Answer: Knowledge-Grounded Dialogue Generation with Adversarial Activated Multi-Reference Learning—0
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data AugmentationCode0
Time Series Synthesis via Multi-scale Patch-based Generation of Wavelet Scalogram—0
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models—0
Bootstrapping NLP tools across low-resourced African languages: an overview and prospects—0
Deep Reinforcement Learning for Inverse Inorganic Materials Design—0
Generative Range Imaging for Learning Scene Priors of 3D LiDAR DataCode1
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation—0
JRDB-Pose: A Large-scale Dataset for Multi-Person Pose Estimation and Tracking—0
Similarity of Neural Architectures using Adversarial Attack Transferability—0
Local intraspecific aggregation in phytoplankton model communities: spatial scales of occurrence and implications for coexistenceCode0
Discovering Many Diverse Solutions with Bayesian OptimizationCode0
Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified RecommendationCode0
Spatio-channel Attention Blocks for Cross-modal Crowd CountingCode1
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