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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 1901–1925 of 9051 papers

TitleStatusHype
Balancing Creativity and Automation: The Influence of AI on Modern Film Production and Dissemination—0
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning—0
MATCHA: Can Multi-Agent Collaboration Build a Trustworthy Conversational Recommender?—0
Offline Learning of Controllable Diverse Behaviors—0
PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts—0
Targeted AMP generation through controlled diffusion with efficient embeddings—0
Latent Video Dataset Distillation—0
Robo-Troj: Attacking LLM-based Task Planners—0
Computational Typology—0
A species of Coprococcus is related to BMI in patients who underwent malabsorptive bariatric surgery and its abundance is modified by magnesium and thiamin intake—0
Agricultural Economics and Innovation in the Inca Empire—0
Bringing Diversity from Diffusion Models to Semantic-Guided Face Asset Generation—0
Surrogate Fitness Metrics for Interpretable Reinforcement Learning—0
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions—0
DialogueAgents: A Hybrid Agent-Based Speech Synthesis Framework for Multi-Party DialogueCode0
Adaptation Method for Misinformation Identification—0
PipeWeaver: Addressing Data Dynamicity in Large Multimodal Model Training with Dynamic Interleaved Pipeline—0
DeepPD: Joint Phase and Object Estimation from Phase Diversity with Neural Calibration of a Deformable Mirror—0
Diverse Prompts: Illuminating the Prompt Space of Large Language Models with MAP-Elites—0
Personalized News Recommendation with Multi-granularity Candidate-aware User Modeling—0
Exploring Language Patterns of Prompts in Text-to-Image Generation and Their Impact on Visual Diversity—0
A Multimodal Recaptioning Framework to Account for Perceptual Diversity in Multilingual Vision-Language Modeling—0
MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space—0
Entropy Rectifying Guidance for Diffusion and Flow Models—0
Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep ClassificationCode0
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