SOTAVerified

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 31263150 of 9051 papers

TitleStatusHype
Closed-loop Error Correction Learning Accelerates Experimental Discovery of Thermoelectric MaterialsCode0
ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials DataCode0
HeteroMorpheus: Universal Control Based on Morphological Heterogeneity ModelingCode0
Enhancing Task-Oriented Dialogues with Chitchat: a Comparative Study Based on Lexical Diversity and DivergenceCode0
Enhancing Symbolic Regression with Quality-Diversity and Physics-Inspired ConstraintsCode0
A hybrid ensemble method with negative correlation learning for regressionCode0
Enhancing Relation Extraction Using Syntactic Indicators and Sentential ContextsCode0
Enhancing Robustness of AI Offensive Code Generators via Data AugmentationCode0
Enhancing Output Diversity Improves Conjugate Gradient-based Adversarial AttacksCode0
Enhancing the Learning Experience: Using Vision-Language Models to Generate Questions for Educational VideosCode0
DAOC: Stable Clustering of Large NetworksCode0
Dank Learning: Generating Memes Using Deep Neural NetworksCode0
Russian Natural Language Generation: Creation of a Language Modelling Dataset and Evaluation with Modern Neural ArchitecturesCode0
Clubmark: a Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA ArchitecturesCode0
Enhancing Feature Diversity Boosts Channel-Adaptive Vision TransformersCode0
Enhancing Image Generation Fidelity via Progressive PromptsCode0
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKACode0
DAM: Diffusion Activation Maximization for 3D Global ExplanationsCode0
Enhancing Molecular Property Prediction via Mixture of Collaborative ExpertsCode0
Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented GuesserCode0
Ethical Considerations for Responsible Data CurationCode0
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous DrivingCode0
FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAGCode0
Group Relative Policy Optimization for Image CaptioningCode0
Reinforcement Learning for Topic ModelsCode0
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