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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 801–825 of 9051 papers

TitleStatusHype
Evaluating and Improving Graph to Text Generation with Large Language ModelsCode0
RELexED: Retrieval-Enhanced Legal Summarization with Exemplar Diversity—0
LeCoPCR: Legal Concept-guided Prior Case Retrieval for European Court of Human Rights cases—0
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series ForecastingCode1
Generating Realistic Forehead-Creases for User Verification via Conditioned Piecewise Polynomial CurvesCode0
Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear BanditsCode0
Co-Learning Bayesian Optimization—0
Deep Modularity Networks with Diversity--Preserving Regularization—0
Adaptive Testing for LLM-Based Applications: A Diversity-based Approach—0
Generative Data Augmentation Challenge: Synthesis of Room Acoustics for Speaker Distance Estimation—0
A Comprehensive Social Bias Audit of Contrastive Vision Language Models—0
Exploring Wikipedia Gender Diversity Over Time x2013 The Wikipedia Gender Dashboard (WGD)—0
Toward Model-centric Heterogeneous Federated Graph Learning: A Knowledge-driven Approach—0
Deep Reinforcement Learning with Hybrid Intrinsic Reward Model—0
Academic Case Reports Lack Diversity: Assessing the Presence and Diversity of Sociodemographic and Behavioral Factors related to Post COVID-19 Condition—0
Foreign object segmentation in chest x-rays through anatomy-guided shape insertion—0
Distributed Multi-Head Learning Systems for Power Consumption Prediction—0
Systematic Abductive Reasoning via Diverse Relation Representations in Vector-symbolic Architecture—0
Approach to Visual Attractiveness of Event Space Through Data-Driven Environment and Spatial Perception—0
Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges—0
Are generative models fair? A study of racial bias in dermatological image generation—0
Curiosity-Driven Reinforcement Learning from Human FeedbackCode1
Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering—0
A New Formulation of Lipschitz Constrained With Functional Gradient Learning for GANsCode4
The impact of intrinsic rewards on exploration in Reinforcement Learning—0
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