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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 3801–3825 of 9051 papers

TitleStatusHype
Let Me Teach You: Pedagogical Foundations of Feedback for Language Models—0
PM-DETR: Domain Adaptive Prompt Memory for Object Detection with Transformers—0
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural NetworksCode1
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load ForecastingCode1
Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letters—0
Policy Space Diversity for Non-Transitive Games—0
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasCode1
Theater Aid System for the Visually Impaired Through Transfer Learning of Spatio-Temporal Graph Convolution Networks—0
Effective Transfer of Pretrained Large Visual Model for Fabric Defect Segmentation via Specifc Knowledge Injection—0
Diversity is Strength: Mastering Football Full Game with Interactive Reinforcement Learning of Multiple AIs—0
Angle Sensitive Pixels for Lensless Imaging on Spherical Sensors—0
Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners—0
Shilling Black-box Review-based Recommender Systems through Fake Review Generation—0
Constraining Generative Models for Engineering Design with Negative DataCode0
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions—0
Pretraining task diversity and the emergence of non-Bayesian in-context learning for regressionCode1
Restart Sampling for Improving Generative ProcessesCode1
Factorised Speaker-environment Adaptive Training of Conformer Speech Recognition Systems—0
Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithms—0
Switch-BERT: Learning to Model Multimodal Interactions by Switching Attention and Input—0
DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited DataCode0
A ground-based dataset and a diffusion model for on-orbit low-light image enhancement—0
A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial DiversityCode0
Is Pre-training Truly Better Than Meta-Learning?—0
Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-StepCode1
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