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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 4401–4450 of 9051 papers

TitleStatusHype
VoxArabica: A Robust Dialect-Aware Arabic Speech Recognition System—0
Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search DecodingCode0
Private Synthetic Data Meets Ensemble Learning—0
SCME: A Self-Contrastive Method for Data-free and Query-Limited Model Extraction Attack—0
CoCoFormer: A controllable feature-rich polyphonic music generation methodCode0
Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer—0
ACES: Generating Diverse Programming Puzzles with with Autotelic Generative Models—0
Graph Neural Network approaches for single-cell data: A recent overview—0
Ultrasound Image Segmentation of Thyroid Nodule via Latent Semantic Feature Co-Registration—0
Incentive Mechanism Design for Distributed Ensemble Learning—0
Dialect Transfer for Swiss German Speech Translation—0
Kernel-Elastic Autoencoder for Molecular Design—0
Evolutionary Dynamic Optimization and Machine Learning—0
Analysing of 3D MIMO Communication Beamforming in Linear and Planar Arrays—0
FedSym: Unleashing the Power of Entropy for Benchmarking the Algorithms for Federated Learning—0
Context-Enhanced Detector For Building Detection From Remote Sensing Images—0
On the Impact of Cross-Domain Data on German Language Models—0
Diversity of Thought Improves Reasoning Abilities of LLMs—0
Diversity for Contingency: Learning Diverse Behaviors for Efficient Adaptation and Transfer—0
Cultural Compass: Predicting Transfer Learning Success in Offensive Language Detection with Cultural FeaturesCode0
SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQACode0
Mitigating stereotypical biases in text to image generative systems—0
RK-core: An Established Methodology for Exploring the Hierarchical Structure within DatasetsCode0
Stochastic Super-resolution of Cosmological Simulations with Denoising Diffusion Models—0
Adversarial optimization leads to over-optimistic security-constrained dispatch, but sampling can help—0
Diversity from Human Feedback—0
Hexa: Self-Improving for Knowledge-Grounded Dialogue System—0
Growing ecosystem of deep learning methods for modeling proteinx2013protein interactions—0
Understanding Transfer Learning and Gradient-Based Meta-Learning TechniquesCode0
Affine Frequency Division Multiplexing With Index Modulation—0
Increasing Entropy to Boost Policy Gradient Performance on Personalization TasksCode0
Enhancing Pre-Trained Language Models with Sentence Position Embeddings for Rhetorical Roles Recognition in Legal Opinions—0
Benchmarking Large Language Models with Augmented Instructions for Fine-grained Information Extraction—0
FM Tone Transfer with Envelope Learning—0
A Holistic Evaluation of Piano Sound Quality—0
QE-BEV: Query Evolution for Bird's Eye View Object Detection in Varied ContextsCode0
Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIsCode0
Knolling Bot: Learning Robotic Object Arrangement from Tidy Demonstrations—0
A Process for Topic Modelling Via Word Embeddings—0
Learning Personalized Alignment for Evaluating Open-ended Text Generation—0
Robustness-Guided Image Synthesis for Data-Free Quantization—0
CLEVRER-Humans: Describing Physical and Causal Events the Human Way—0
Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries—0
Unbiased estimation of sampling variance for Simpson's diversity indexCode0
MUNCH: Modelling Unique 'N Controllable Heads—0
A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization—0
Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data—0
scHyena: Foundation Model for Full-Length Single-Cell RNA-Seq Analysis in Brain—0
Hire When You Need to: Gradual Participant Recruitment for Auction-based Federated Learning—0
Exploring Model Learning Heterogeneity for Boosting Ensemble RobustnessCode0
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