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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 5701–5725 of 9051 papers

TitleStatusHype
Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models—0
The Paradox of Stochasticity: Limited Creativity and Computational Decoupling in Temperature-Varied LLM Outputs of Structured Fictional Data—0
The Past as a Stochastic Process—0
The placement of the head that maximizes predictability. An information theoretic approach—0
The Price of Diversity—0
The Price of Quota-based Diversity in Assignment Problems—0
The Promise of Cross-Species Coexpression Analysis in Studying the Coevolution and Ecology of Host-Symbiont Interactions—0
The Prompt Alchemist: Automated LLM-Tailored Prompt Optimization for Test Case Generation—0
The PV-ALE Dataset: Enhancing Apple Leaf Disease Classification Through Transfer Learning with Convolutional Neural Networks—0
The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformers—0
There Is No Standard Answer: Knowledge-Grounded Dialogue Generation with Adversarial Activated Multi-Reference Learning—0
The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Out-of-Distribution Robustness—0
Thermodynamic competition between membrane protein oligomeric states—0
Thermodynamic constraints on the assembly and diversity of microbial ecosystems are different near to and far from equilibrium—0
Thermodynamic limit in learning period three—0
The Robustness Limits of SoTA Vision Models to Natural Variation—0
The role of attraction-repulsion dynamics in simulating the emergence of inflectional class systems—0
The Role of Bias in News Recommendation in the Perception of the Covid-19 Pandemic—0
The Role of Diverse Replay for Generalisation in Reinforcement Learning—0
The Role of Diversity in In-Context Learning for Large Language Models—0
The Role of Domain Randomization in Training Diffusion Policies for Whole-Body Humanoid Control—0
The role of inhibitory neuronal variability in modulating phase diversity between coupled networks—0
The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search—0
The Role of Predictive Uncertainty and Diversity in Embodied AI and Robot Learning—0
The Role of Text-to-Image Models in Advanced Style Transfer Applications: A Case Study with DALL-E 3—0
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