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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 8251–8300 of 9051 papers

TitleStatusHype
Complete 3D Scene Parsing from an RGBD ImageCode0
Generating Language Corrections for Teaching Physical Control TasksCode0
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based OptimizationCode0
Smoothing Entailment Graphs with Language ModelsCode0
Competition and Diversity in Generative AICode0
Generating Informative and Diverse Conversational Responses via Adversarial Information MaximizationCode0
The Diversity-Innovation Paradox in ScienceCode0
A Simple, Fast Diverse Decoding Algorithm for Neural GenerationCode0
Diversity-Based Generalization for Unsupervised Text Classification under Domain ShiftCode0
A Comprehensive Evaluation on Event Reasoning of Large Language ModelsCode0
Diversity-based Deep Reinforcement Learning Towards Multidimensional Difficulty for Fighting Game AICode0
Provable and Efficient Continual Representation LearningCode0
Adversarially Diversified Rehearsal Memory (ADRM): Mitigating Memory Overfitting Challenge in Continual LearningCode0
In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator LearningCode0
When Box Meets Graph Neural Network in Tag-aware RecommendationCode0
Comparison of Diverse Decoding Methods from Conditional Language ModelsCode0
Local Padding in Patch-Based GANs for Seamless Infinite-Sized Texture SynthesisCode0
Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image CaptioningCode0
Measuring Policy Distance for Multi-Agent Reinforcement LearningCode0
The Effect of Diversity in Meta-LearningCode0
Measuring the Diversity of Automatic Image DescriptionsCode0
Prune and Tune Ensembles: Low-Cost Ensemble Learning With Sparse Independent SubnetworksCode0
Diversity-Aware Weighted Majority Vote Classifier for Imbalanced DataCode0
Generating Diverse Descriptions from Semantic GraphsCode0
Pruning Techniques for Mixed Ensembles of Genetic Programming ModelsCode0
Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search DecodingCode0
The effect of diversity on group decision-makingCode0
Generating Diverse and Meaningful CaptionsCode0
PSDet: Efficient and Universal Parking Slot DetectionCode0
A Block-Based Adaptive Decoupling Framework for Graph Neural NetworksCode0
Social and environmental impact of recent developments in machine learning on biology and chemistry researchCode0
Generating Diverse and High-Quality Texts by Minimum Bayes Risk DecodingCode0
A simple and effective hybrid genetic search for the job sequencing and tool switching problemCode0
PSP: Million-level Protein Sequence Dataset for Protein Structure PredictionCode0
Generating Diverse and Accurate Visual Captions by Comparative Adversarial LearningCode0
Comparative evaluation of 2D feature correspondence selection algorithmsCode0
Diversity Aware Relevance Learning for Argument SearchCode0
Adversarial Inference for Multi-Sentence Video DescriptionCode0
COMET: Coverage-guided Model Generation For Deep Learning Library TestingCode0
Batch Active Learning at ScaleCode0
Memory-Optimized Once-For-All NetworkCode0
Toward Improving Coherence and Diversity of Slogan GenerationCode0
Generating Automatically Print/Scan Textures for Morphing Attack Detection ApplicationsCode0
Diversity in deep generative models and generative AICode0
Diversity-Aware Coherence Loss for Improving Neural Topic ModelsCode0
Wasserstein Expansible Variational Autoencoder for Discriminative and Generative Continual LearningCode0
Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in HanabiCode0
Generate then Refine: Data Augmentation for Zero-shot Intent DetectionCode0
Generalized Face Anti-spoofing via Finer Domain Partition and Disentangling Liveness-irrelevant FactorsCode0
Adversarial Imitation Learning with Trajectorial Augmentation and CorrectionCode0
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