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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 5951–6000 of 9051 papers

TitleStatusHype
Neural networks for semantic segmentation of historical city maps: Cross-cultural performance and the impact of figurative diversity—0
Neural Network Verification for the Masses (of AI graduates)—0
Neural representation and generation for RNA secondary structures—0
Neural Response Generation via GAN with an Approximate Embedding Layer—0
Neural Response Generation with Meta-Words—0
Neural Story Planning—0
Assessing fish abundance from underwater video using deep neural networks—0
Assessing Distractors in Multiple-Choice Tests—0
Neural Text Generation: Past, Present and Beyond—0
UAV 3-D path planning based on MOEA/D with adaptive areal weight adjustment—0
Neural Text Summarization: A Critical Evaluation—0
Neural User Simulation for Corpus-based Policy Optimisation of Spoken Dialogue Systems—0
Neural User Simulation for Corpus-based Policy Optimisation for Spoken Dialogue Systems—0
ASR4REAL: An extended benchmark for speech models—0
A Classifier-free Ensemble Selection Method based on Data Diversity in Random Subspaces—0
A Spiking Neuron Synaptic Plasticity Model Optimized for Unsupervised Learning—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
Neuronal heterogeneity modulates phase-synchronization between unidirectionally coupled populations with excitation-inhibition balance—0
Neuro-Symbolic Data Generation for Math Reasoning—0
Neutral Diversity in Experimental Metapopulations—0
Neutral phylogenetic models and their role in tree-based biodiversity measures—0
Neutral theory of cooperators—0
A Song of Ice and Fire: Analyzing Textual Autotelic Agents in ScienceWorld—0
New Classes of the Greedy-Applicable Arm Feature Distributions in the Sparse Linear Bandit Problem—0
New confidence interval methods for Shannon index—0
When One LLM Drools, Multi-LLM Collaboration Rules—0
New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking—0
New expressions on the performance of a novel multi-hop relay-assisted hybrid FSO / RF communication system with receive diversity—0
A Classification-Based Study of Covariate Shift in GAN Distributions—0
When should agents explore?—0
New thoughts on an old riddle: what determines genetic diversity within and between species?—0
Niche differentiation in the light spectrum promotes coexistence of phytoplankton species: a spatial modelling approach—0
A Classification-Based Perspective on GAN Distributions—0
Niching Diversity Estimation for Multi-modal Multi-objective Optimization—0
NightCC: Nighttime Color Constancy via Adaptive Channel Masking—0
Nitrogen-induced hysteresis in grassland biodiversity: a theoretical test of litter-mediated mechanisms—0
A small Griko-Italian speech translation corpus—0
A Small but Informed and Diverse Model: The Case of the Multimodal GuessWhat!? Guessing Game—0
Language Varieties of Italy: Technology Challenges and Opportunities—0
UCTGAN: Diverse Image Inpainting Based on Unsupervised Cross-Space Translation—0
No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World—0
A Chinese Continuous Sign Language Dataset Based on Complex Environments—0
NOD-TAMP: Generalizable Long-Horizon Planning with Neural Object Descriptors—0
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models—0
As long as you talk about me: The importance of family firm brands and the contingent role of family-firm identity—0
Noise Consistency Regularization for Improved Subject-Driven Image Synthesis—0
Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning—0
Ask to Understand: Question Generation for Multi-hop Question Answering—0
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization—0
Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification—0
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