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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

Showing 81268150 of 9051 papers

TitleStatusHype
Does RoBERTa Perform Better than BERT in Continual Learning: An Attention Sink PerspectiveCode0
Towards Multiple References Era -- Addressing Data Leakage and Limited Reference Diversity in NLG EvaluationCode0
Single Domain Generalization for Alzheimer's Detection from 3D MRIs with Pseudo-Morphological Augmentations and Contrastive LearningCode0
Machine Translation of Low-Resource Spoken Dialects: Strategies for Normalizing Swiss GermanCode0
Probabilistic models of genetic variation in structured populations applied to global human studiesCode0
Macroscopic properties of equity markets: stylized facts and portfolio performanceCode0
MAD-EN: Microarchitectural Attack Detection through System-wide Energy ConsumptionCode0
DMix: Adaptive Distance-aware Interpolative MixupCode0
Gram-Elites: N-Gram Based Quality-Diversity SearchCode0
Gradient Estimators for Implicit ModelsCode0
DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender SystemsCode0
MAGID: An Automated Pipeline for Generating Synthetic Multi-modal DatasetsCode0
MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identificationCode0
GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and DovesCode0
Maintaining diversity in structured populationsCode0
The BIAS Detection Framework: Bias Detection in Word Embeddings and Language Models for European LanguagesCode0
MaizeField3D: A Curated 3D Point Cloud and Procedural Model Dataset of Field-Grown Maize from a Diversity PanelCode0
A Contextual Bandit Bake-offCode0
DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR StrategyCode0
Divide and not forget: Ensemble of selectively trained experts in Continual LearningCode0
DIVE: Towards Descriptive and Diverse Visual Commonsense GenerationCode0
Probing Contextual Diversity for Dense Out-of-Distribution DetectionCode0
GPoeT-2: A GPT-2 Based Poem GeneratorCode0
Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical StudyCode0
Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity PragmaticsCode0
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