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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 1901–1925 of 9051 papers

TitleStatusHype
Cosine Similarity of Multimodal Content Vectors for TV Programmes—0
Cosmic radiation drives quasi-periodic changes in the diversity of siliceous marine microplankton—0
DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement—0
Assessing Social Determinants-Related Performance Bias of Machine Learning Models: A case of Hyperchloremia Prediction in ICU Population—0
Cost-Effective Cyber-Physical System Prototype for Precision Agriculture with a Focus on Crop Growth—0
Attribute analysis with synthetic dataset for person re-identification—0
Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization—0
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization—0
Assessing Social Alignment: Do Personality-Prompted Large Language Models Behave Like Humans?—0
Considerations for Ethical Speech Recognition Datasets—0
AI-based Reconstruction for Fast MRI -- A Systematic Review and Meta-analysis—0
Counting and optimising maximum phylogenetic diversity sets—0
Deep Reinforcement Learning with Hybrid Intrinsic Reward Model—0
CourseGPT-zh: an Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimization—0
Conservative Exploration using Interleaving—0
Consecutive Question Generation with Multitask Joint Reranking and Dynamic Rationale Search—0
Covariance Matrix Adaptation MAP-Annealing—0
Assessing Quality-Diversity Neuro-Evolution Algorithms Performance in Hard Exploration Problems—0
Connecting User and Item Perspectives in Popularity Debiasing for Collaborative Recommendation—0
Assessing Intra-class Diversity and Quality of Synthetically Generated Images in a Biomedical and Non-biomedical Setting—0
A Tutorial On Intersectionality in Fair Rankings—0
CPLM, a Parallel Corpus for Mexican Languages: Development and Interface—0
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation—0
CrashAgent: Crash Scenario Generation via Multi-modal Reasoning—0
AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI—0
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