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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 2301–2325 of 9051 papers

TitleStatusHype
Evaluating and Improving Graph to Text Generation with Large Language ModelsCode0
Feature-based Evolutionary Diversity Optimization of Discriminating Instances for Chance-constrained Optimization Problems—0
E-Gen: Leveraging E-Graphs to Improve Continuous Representations of Symbolic ExpressionsCode0
RELexED: Retrieval-Enhanced Legal Summarization with Exemplar Diversity—0
Co-Learning Bayesian Optimization—0
LeCoPCR: Legal Concept-guided Prior Case Retrieval for European Court of Human Rights cases—0
Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear BanditsCode0
Adaptive Testing for LLM-Based Applications: A Diversity-based Approach—0
Generating Realistic Forehead-Creases for User Verification via Conditioned Piecewise Polynomial CurvesCode0
Deep Modularity Networks with Diversity--Preserving Regularization—0
Generative Data Augmentation Challenge: Synthesis of Room Acoustics for Speaker Distance Estimation—0
Exploring Wikipedia Gender Diversity Over Time x2013 The Wikipedia Gender Dashboard (WGD)—0
A Comprehensive Social Bias Audit of Contrastive Vision Language Models—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
Distributed Multi-Head Learning Systems for Power Consumption Prediction—0
Systematic Abductive Reasoning via Diverse Relation Representations in Vector-symbolic Architecture—0
Foreign object segmentation in chest x-rays through anatomy-guided shape insertion—0
Optimizing Pretraining Data Mixtures with LLM-Estimated Utility—0
The impact of intrinsic rewards on exploration in Reinforcement Learning—0
Are generative models fair? A study of racial bias in dermatological image generation—0
Embedding-Driven Diversity Sampling to Improve Few-Shot Synthetic Data Generation—0
Approach to Visual Attractiveness of Event Space Through Data-Driven Environment and Spatial Perception—0
Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering—0
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