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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 2476–2500 of 9051 papers

TitleStatusHype
Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision TransformersCode0
GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language UnderstandingCode0
BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language ModelsCode0
Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data LimitationsCode0
Beyond a Single Mode: GAN Ensembles for Diverse Medical Data GenerationCode0
GDPP: Learning Diverse Generations Using Determinantal Point ProcessCode0
Beyond Aesthetics: Cultural Competence in Text-to-Image ModelsCode0
Sequential Recommendation with Controllable Diversification: Representation Degeneration and DiversityCode0
GAIT: A Geometric Approach to Information TheoryCode0
"Garbage In, Garbage Out" Revisited: What Do Machine Learning Application Papers Report About Human-Labeled Training Data?Code0
An Effective Deployment of Diffusion LM for Data Augmentation in Low-Resource Sentiment ClassificationCode0
GAN-GA: A Generative Model based on Genetic Algorithm for Medical Image GenerationCode0
DiffuCOMET: Contextual Commonsense Knowledge DiffusionCode0
Fully Automatic Video Colorization with Self-Regularization and DiversityCode0
Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly DetectionCode0
FuncGenFoil: Airfoil Generation and Editing Model in Function SpaceCode0
Guylingo: The Republic of Guyana Creole CorporaCode0
Beware the Black-Box: on the Robustness of Recent Defenses to Adversarial ExamplesCode0
Dissecting CLIP: Decomposition with a Schur Complement-based ApproachCode0
FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing FlowCode0
A Chit-Chats Enhanced Task-Oriented Dialogue Corpora for Fuse-Motive Conversation SystemsCode0
Full-Stack Filters to Build Minimum Viable CNNsCode0
G2GT: Retrosynthesis Prediction with Graph to Graph Attention Neural Network and Self-TrainingCode0
From structure mining to unsupervised exploration of atomic octahedral networksCode0
Difficulty-aware Image Super Resolution via Deep Adaptive Dual-NetworkCode0
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