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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 5701–5725 of 9051 papers

TitleStatusHype
Syntactically Diverse Adversarial Network for Knowledge-Grounded Conversation Generation—0
Task-Oriented Clustering for DialoguesCode0
Diversity and Consistency: Exploring Visual Question-Answer Pair Generation—0
Coreference Chains Categorization by Sequence Clustering—0
PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and ClassificationCode1
Using Synthetic Images To Uncover Population Biases In Facial Landmarks Detection—0
Improving Contrastive Learning on Imbalanced Seed Data via Open-World SamplingCode1
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training—0
Learning Debiased and Disentangled Representations for Semantic Segmentation—0
FairER: Entity Resolution with Fairness ConstraintsCode0
Angle Diversity Trasmitter For High Speed Data Center Uplink Communications—0
Diversity-Driven Combination for Grammatical Error CorrectionCode0
D2RLIR : an improved and diversified ranking function in interactive recommendation systems based on deep reinforcement learning—0
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning—0
Wasserstein Distance Maximizing Intrinsic Control—0
MEmoBERT: Pre-training Model with Prompt-based Learning for Multimodal Emotion Recognition—0
The chemical space of terpenes: insights from data science and AICode1
Diversity Enhanced Active Learning with Strictly Proper Scoring RulesCode1
Diversity Matters When Learning From Ensembles—0
Separating Content and Style for Unsupervised Image-to-Image TranslationCode0
A novel multiobjective evolutionary algorithm based on decomposition and multi-reference points strategy—0
Learning Diverse Policies in MOBA Games via Macro-Goals—0
Local and collective transitions in sparsely-interacting ecological communities—0
Ensemble Federated Adversarial Training with Non-IID data—0
Robustness of Graph Neural Networks at ScaleCode1
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