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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 7651–7700 of 9051 papers

TitleStatusHype
Pareto Front-Diverse Batch Multi-Objective Bayesian OptimizationCode0
Analysis of the first Genetic Engineering Attribution ChallengeCode0
BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language ModelsCode0
Guardian of the Ensembles: Introducing Pairwise Adversarially Robust Loss for Resisting Adversarial Attacks in DNN EnsemblesCode0
Seed banks can help to maintain the diversity of interacting phytoplankton speciesCode0
Tailoring Mixup to Data for CalibrationCode0
Curls & Whey: Boosting Black-Box Adversarial AttacksCode0
CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement LearningCode0
Tailoring Self-Rationalizers with Multi-Reward DistillationCode0
Beyond Task Diversity: Provable Representation Transfer for Sequential Multi-Task Linear BanditsCode0
Increasing diversity of omni-directional images generated from single image using cGAN based on MLPMixerCode0
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?Code0
Knowledge Graph Context-Enhanced Diversified RecommendationCode0
In Conclusion Not Repetition: Comprehensive Abstractive Summarization With Diversified Attention Based On Determinantal Point ProcessesCode0
InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender DiversityCode0
Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon SetCode0
Knowledge of cultural moral norms in large language modelsCode0
Enhanced Memory Network: The novel network structure for Symbolic Music GenerationCode0
Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer SatisfactionCode0
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning ArchitectureCode0
Improved Paraphrase Generation via Controllable Latent DiffusionCode0
End-to-end Adversarial Learning for Generative Conversational AgentsCode0
Improving Unsupervised Relation Extraction by Augmenting Diverse Sentence PairsCode0
Improving Transferability of Adversarial Examples with Input DiversityCode0
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region FittingCode0
Improving the Evaluation of Generative Models with Fuzzy LogicCode0
Seeking Quality Diversity in Evolutionary Co-design of Morphology and Control of Soft Tensegrity Modular RobotsCode0
Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial African Creole LanguagesCode0
Encourage or Inhibit Monosemanticity? Revisit Monosemanticity from a Feature Decorrelation PerspectiveCode0
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial TrainingCode0
Curiosity Driven Exploration of Learned Disentangled Goal SpacesCode0
Beyond Factual Accuracy: Evaluating Coverage of Diverse Factual Information in Long-form Text GenerationCode0
Improving the Diversity of Unsupervised Paraphrasing with Embedding OutputsCode0
SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQACode0
Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding ExplorationCode0
Towards a Systematic Approach to Design New Ensemble Learning AlgorithmsCode0
PathGAN: Local Path Planning with Attentive Generative Adversarial NetworksCode0
LADIMO: Face Morph Generation through Biometric Template Inversion with Latent DiffusionCode0
LAD: Language Models as Data for Zero-Shot DialogCode0
Improving Screening Processes via Calibrated Subset SelectionCode0
LAHAJA: A Robust Multi-accent Benchmark for Evaluating Hindi ASR SystemsCode0
LaiDA: Linguistics-aware In-context Learning with Data Augmentation for Metaphor Components IdentificationCode0
A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddingsCode0
Improving Neural Response Diversity with Frequency-Aware Cross-Entropy LossCode0
Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing GenerationCode0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-TranslationCode0
Improving Neural Language Modeling via Adversarial TrainingCode0
Curiosity as a Self-Supervised Method to Improve Exploration in De novo Drug DesignCode0
Beyond Digital "Echo Chambers": The Role of Viewpoint Diversity in Political DiscussionCode0
Segmenting Medical Images with Limited DataCode0
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