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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 8801–8850 of 9051 papers

TitleStatusHype
DI2: prior-free and multi-item discretization ofbiomedical data and its applicationsCode0
dhSegment: A generic deep-learning approach for document segmentationCode0
Automatic Identification of Traditional Colombian Music Genres based on Audio Content Analysis and Machine Learning TechniqueCode0
DGSAN: Discrete Generative Self-Adversarial NetworkCode0
Rethinking Mitosis Detection: Towards Diverse Data and Feature RepresentationCode0
A Deep Learning Approach to Private Data Sharing of Medical Images Using Conditional GANsCode0
DFPE: A Diverse Fingerprint Ensemble for Enhancing LLM PerformanceCode0
Unveiling the Mystery of Visual Attributes of Concrete and Abstract Concepts: Variability, Nearest Neighbors, and Challenging CategoriesCode0
Rethinking Robustness of Model AttributionsCode0
Vision-and-Language PretrainingCode0
Rethinking Self-driving: Multi-task Knowledge for Better Generalization and Accident Explanation AbilityCode0
No Offense Taken: Eliciting Offensiveness from Language ModelsCode0
Exploring Format Consistency for Instruction TuningCode0
Automatic Generation of Word Problems for Academic Education via Natural Language Processing (NLP)Code0
Rethinking the transfer learning for FCN based polyp segmentation in colonoscopyCode0
Normalized DiversificationCode0
Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with ExplainabilityCode0
Rethinking Time Encoding via Learnable Transformation FunctionsCode0
Rethinking Token Reduction with Parameter-Efficient Fine-Tuning in ViT for Pixel-Level TasksCode0
Exploring Flat Minima for Domain Generalization with Large Learning RatesCode0
A Guide for Practical Use of ADMG Causal Data AugmentationCode0
TVM: An Automated End-to-End Optimizing Compiler for Deep LearningCode0
Novel Policy Seeking with Constrained OptimizationCode0
Cascading CMA-ES Instances for Generating Input-diverse Solution BatchesCode0
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement LearningCode0
Exploring Diversity in Back Translation for Low-Resource Machine TranslationCode0
A*3D Dataset: Towards Autonomous Driving in Challenging EnvironmentsCode0
DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine ModelCode0
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous DrivingCode0
Exploratory State Representation LearningCode0
NusaBERT: Teaching IndoBERT to be Multilingual and MulticulturalCode0
Exploiting ConvNet Diversity for Flooding IdentificationCode0
Explaining crime diversity with Google street viewCode0
A Deep Generative Artificial Intelligence system to decipher species coexistence patternsCode0
Twin Auxilary Classifiers GANCode0
Carbohydrate NMR chemical shift predictions using E(3) equivariant graph neural networksCode0
Capturing the diversity of multilingual societiesCode0
ExplainCPE: A Free-text Explanation Benchmark of Chinese Pharmacist ExaminationCode0
Expanding, Retrieving and Infilling: Diversifying Cross-Domain Question Generation with Flexible TemplatesCode0
Twin Auxiliary Classifiers GANCode0
Expanding functional protein sequence space using generative adversarial networksCode0
Privacy-preserving datasets by capturing feature distributions with Conditional VAEsCode0
Time-to-Pattern: Information-Theoretic Unsupervised Learning for Scalable Time Series SummarizationCode0
Style Outweighs Substance: Failure Modes of LLM Judges in Alignment BenchmarkingCode0
Style-Restricted GAN: Multi-Modal Translation with Style Restriction Using Generative Adversarial NetworksCode0
Exhaustive Exploitation of Nature-inspired Computation for Cancer Screening in an Ensemble MannerCode0
Developing parsimonious ensembles using predictor diversity within a reinforcement learning frameworkCode0
Determinantal Point Process as an alternative to NMSCode0
Can Users Detect Biases or Factual Errors in Generated Responses in Conversational Information-Seeking?Code0
Revealing the Shape of Genome Space via K-mer TopologyCode0
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