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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 3401–3425 of 9051 papers

TitleStatusHype
Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active ExplorationCode1
Ultrasound Image Segmentation of Thyroid Nodule via Latent Semantic Feature Co-Registration—0
Dialect Transfer for Swiss German Speech Translation—0
Incentive Mechanism Design for Distributed Ensemble Learning—0
Analysing of 3D MIMO Communication Beamforming in Linear and Planar Arrays—0
Evolutionary Dynamic Optimization and Machine Learning—0
Kernel-Elastic Autoencoder for Molecular Design—0
Towards Evaluating Generalist Agents: An Automated Benchmark in Open WorldCode1
D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data PruningCode1
CRITERIA: a New Benchmarking Paradigm for Evaluating Trajectory Prediction Models for Autonomous DrivingCode3
TabLib: A Dataset of 627M Tables with ContextCode1
FedSym: Unleashing the Power of Entropy for Benchmarking the Algorithms for Federated Learning—0
Learning a Cross-modality Anomaly Detector for Remote Sensing ImageryCode1
On the Impact of Cross-Domain Data on German Language Models—0
Context-Enhanced Detector For Building Detection From Remote Sensing Images—0
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive TestingCode1
Diversity of Thought Improves Reasoning Abilities of LLMs—0
Diversity for Contingency: Learning Diverse Behaviors for Efficient Adaptation and Transfer—0
ADASR: An Adversarial Auto-Augmentation Framework for Hyperspectral and Multispectral Data FusionCode1
RK-core: An Established Methodology for Exploring the Hierarchical Structure within DatasetsCode0
Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models—0
Mitigating stereotypical biases in text to image generative systems—0
Adversarial optimization leads to over-optimistic security-constrained dispatch, but sampling can help—0
Score-Based Generative Models for Designing Binding Peptide BackbonesCode1
Cultural Compass: Predicting Transfer Learning Success in Offensive Language Detection with Cultural FeaturesCode0
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