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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 1751–1800 of 9051 papers

TitleStatusHype
Is Limited Participant Diversity Impeding EEG-based Machine Learning?Code0
Conditional Quantile Estimation for Uncertain Watch Time in Short-Video RecommendationCode0
INGB: Informed Nonlinear Granular Ball Oversampling Framework for Noisy Imbalanced ClassificationCode0
Input-gradient space particle inference for neural network ensemblesCode0
Information-Seeking Decision Strategies Mitigate Risk in Dynamic, Uncertain EnvironmentsCode0
Conditional Diffusion Models with Classifier-Free Gibbs-like GuidanceCode0
InfoDiffusion: Information Entropy Aware Diffusion Process for Non-Autoregressive Text GenerationCode0
Information Density Principle for MLLM BenchmarksCode0
Information-Theoretic Active Learning for Content-Based Image RetrievalCode0
InsBank: Evolving Instruction Subset for Ongoing AlignmentCode0
Concise and interpretable multi-label rule setsCode0
Inference of cell dynamics on perturbation data using adjoint sensitivityCode0
Influence Maximization in Hypergraphs using Multi-Objective Evolutionary AlgorithmsCode0
IndicEval-XL: Bridging Linguistic Diversity in Code Generation Across Indic LanguagesCode0
Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic ManuscriptsCode0
In-distribution Public Data Synthesis with Diffusion Models for Differentially Private Image ClassificationCode0
Insect Identification in the Wild: The AMI DatasetCode0
In Conclusion Not Repetition: Comprehensive Abstractive Summarization With Diversified Attention Based On Determinantal Point ProcessesCode0
Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical StudyCode0
Integrating LLMs and Decision Transformers for Language Grounded Generative Quality-DiversityCode0
Confidence-weighted integration of human and machine judgments for superior decision-makingCode0
A Hybrid Retrieval-Generation Neural Conversation ModelCode0
InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender DiversityCode0
Interactive Constrained MAP-Elites: Analysis and Evaluation of the Expressiveness of the Feature DimensionsCode0
Increasing diversity of omni-directional images generated from single image using cGAN based on MLPMixerCode0
A Block-Based Adaptive Decoupling Framework for Graph Neural NetworksCode0
Concept-as-Tree: Synthetic Data is All You Need for VLM PersonalizationCode0
ComSD: Balancing Behavioral Quality and Diversity in Unsupervised Skill DiscoveryCode0
Increasing Entropy to Boost Policy Gradient Performance on Personalization TasksCode0
Computing recommendations via a Knowledge Graph-aware AutoencoderCode0
A Simple Yet Effective Approach for Diversified Session-Based RecommendationCode0
Improving Transferability of Adversarial Examples with Input DiversityCode0
Active Learning for Abstractive Text SummarizationCode0
Consistency-based anomaly detection with adaptive multiple-hypotheses predictionsCode0
Improving Unsupervised Relation Extraction by Augmenting Diverse Sentence PairsCode0
Assessing the Impact of Music Recommendation Diversity on Listeners: A Longitudinal StudyCode0
Incubating Text Classifiers Following User Instruction with Nothing but LLMCode0
Improving the Diversity of Unsupervised Paraphrasing with Embedding OutputsCode0
Is Depth All You Need? An Exploration of Iterative Reasoning in LLMsCode0
A Simple Method for Commonsense ReasoningCode0
Improving the Evaluation of Generative Models with Fuzzy LogicCode0
A Hierarchical Deep Learning Approach for Minority Instrument DetectionCode0
Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding ExplorationCode0
A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddingsCode0
A Structure-Guided Diffusion Model for Large-Hole Image CompletionCode0
A Simple, Fast Diverse Decoding Algorithm for Neural GenerationCode0
To Ensemble or Not Ensemble: When does End-To-End Training Fail?Code0
JoTR: A Joint Transformer and Reinforcement Learning Framework for Dialog Policy LearningCode0
Computational detection of antigen specific B cell receptors following immunizationCode0
Improving Screening Processes via Calibrated Subset SelectionCode0
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