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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 1701–1750 of 9051 papers

TitleStatusHype
Investigating the Influence of Prompt-Specific Shortcuts in AI Generated Text DetectionCode0
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic lossCode0
Investigating Evaluation of Open-Domain Dialogue Systems With Human Generated Multiple ReferencesCode0
In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across LanguagesCode0
Is Feature Diversity Necessary in Neural Network Initialization?Code0
Jacquard: A Large Scale Dataset for Robotic Grasp DetectionCode0
Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and LimitationsCode0
Intrinsically-Motivated Humans and Agents in Open-World ExplorationCode0
Interactive Constrained MAP-Elites: Analysis and Evaluation of the Expressiveness of the Feature DimensionsCode0
AI-enhanced Collective IntelligenceCode0
Interactive Image Segmentation With Latent DiversityCode0
Result Diversification in Search and Recommendation: A SurveyCode0
A Survey of Data Synthesis ApproachesCode0
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data AnnotationsCode0
Interactive Neural Style Transfer with ArtistsCode0
Integrating Present and Past in Unsupervised Continual LearningCode0
Integrating LLMs and Decision Transformers for Language Grounded Generative Quality-DiversityCode0
Intent Factored Generation: Unleashing the Diversity in Your Language ModelCode0
Active Learning in Genetic Programming: Guiding Efficient Data Collection for Symbolic RegressionCode0
Intentional Computational Level DesignCode0
A Structure-Guided Diffusion Model for Large-Hole Image CompletionCode0
InstaSynth: Opportunities and Challenges in Generating Synthetic Instagram Data with ChatGPT for Sponsored Content DetectionCode0
Instance-wise Supervision-level Optimization in Active LearningCode0
LADIMO: Face Morph Generation through Biometric Template Inversion with Latent DiffusionCode0
MGL2Rank: Learning to Rank the Importance of Nodes in Road Networks Based on Multi-Graph FusionCode0
Input-gradient space particle inference for neural network ensemblesCode0
InsBank: Evolving Instruction Subset for Ongoing AlignmentCode0
Assessing the Impact of Music Recommendation Diversity on Listeners: A Longitudinal StudyCode0
Active Learning for Regression Using Greedy SamplingCode0
Insect Identification in the Wild: The AMI DatasetCode0
Information-Theoretic Active Learning for Content-Based Image RetrievalCode0
Information-Seeking Decision Strategies Mitigate Risk in Dynamic, Uncertain EnvironmentsCode0
INGB: Informed Nonlinear Granular Ball Oversampling Framework for Noisy Imbalanced ClassificationCode0
Information Density Principle for MLLM BenchmarksCode0
A Block-Based Adaptive Decoupling Framework for Graph Neural NetworksCode0
Inference of cell dynamics on perturbation data using adjoint sensitivityCode0
A Hybrid Retrieval-Generation Neural Conversation ModelCode0
Influence Maximization in Hypergraphs using Multi-Objective Evolutionary AlgorithmsCode0
Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical StudyCode0
A Hybrid Genetic Algorithm for the Traveling Salesman Problem with DroneCode0
In-distribution Public Data Synthesis with Diffusion Models for Differentially Private Image ClassificationCode0
Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic ManuscriptsCode0
InfoDiffusion: Information Entropy Aware Diffusion Process for Non-Autoregressive Text GenerationCode0
Increasing diversity of omni-directional images generated from single image using cGAN based on MLPMixerCode0
In Conclusion Not Repetition: Comprehensive Abstractive Summarization With Diversified Attention Based On Determinantal Point ProcessesCode0
Increasing Entropy to Boost Policy Gradient Performance on Personalization TasksCode0
InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender DiversityCode0
Incubating Text Classifiers Following User Instruction with Nothing but LLMCode0
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region FittingCode0
Improving Transferability of Adversarial Examples with Input DiversityCode0
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