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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 5101–5125 of 9051 papers

TitleStatusHype
Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management—0
Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno Effect—0
Learning temporal relationships between symbols with Laplace Neural Manifolds—0
Metropolis Theorem and Its Applications in Single Image Detail EnhancementCode0
Towards Radar Emitter Recognition in Changing Environments with Domain Generalization—0
One-Pot Multi-Frame Denoising—0
Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord Questions—0
OTFS Signaling for SCMA With Coordinated Multi-Point Vehicle Communications—0
Counting Carbon: A Survey of Factors Influencing the Emissions of Machine LearningCode0
Defect Transfer GAN: Diverse Defect Synthesis for Data Augmentation—0
Reanalyzing L2 Preposition Learning with Bayesian Mixed Effects and a Pretrained Language ModelCode0
On time-consistent equilibrium stopping under aggregation of diverse discount rates—0
Conversational AI-Powered Design: ChatGPT as Designer, User, and Product—0
Generative Oversampling for Imbalanced Data via Majority-Guided VAE—0
A Friendly Face: Do Text-to-Image Systems Rely on Stereotypes when the Input is Under-Specified?—0
The Stable Entropy Hypothesis and Entropy-Aware Decoding: An Analysis and Algorithm for Robust Natural Language Generation—0
Diminished Diversity-of-Thought in a Standard Large Language Model—0
Why Can't Discourse Parsing Generalize? A Thorough Investigation of the Impact of Data DiversityCode0
Evaluation of Word Embeddings for the Social Sciences—0
Large Scale Multi-Lingual Multi-Modal Summarization DatasetCode0
Autoselection of the Ensemble of Convolutional Neural Networks with Second-Order Cone ProgrammingCode0
Interpretable Diversity Analysis: Visualizing Feature Representations In Low-Cost Ensembles—0
Sparse Mutation Decompositions: Fine Tuning Deep Neural Networks with Subspace Evolution—0
A Song of Ice and Fire: Analyzing Textual Autotelic Agents in ScienceWorld—0
Active Simultaneously Transmitting and Reflecting (STAR)-RISs: Modelling and Analysis—0
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