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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 2101–2150 of 9051 papers

TitleStatusHype
GANmut: Generating and Modifying Facial Expressions—0
Improving Adversarial Robustness via Decoupled Visual Representation MaskingCode0
STAR: Scale-wise Text-to-image generation via Auto-Regressive representationsCode2
Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation—0
Unlocking Large Language Model's Planning Capabilities with Maximum Diversity Fine-tuning—0
Consistency-diversity-realism Pareto fronts of conditional image generative modelsCode2
Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata EcosystemsCode1
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian LanguagesCode2
Linear Contextual Bandits with Hybrid Payoff: RevisitedCode0
LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal DataCode1
Heterogeneous Federated Learning with Convolutional and Spiking Neural Networks—0
Annotation Cost-Efficient Active Learning for Deep Metric Learning Driven Remote Sensing Image Retrieval—0
Data Ethics in the Era of Healthcare Artificial Intelligence in Africa: An Ubuntu Philosophy Perspective—0
T-JEPA: A Joint-Embedding Predictive Architecture for Trajectory Similarity Computation—0
Contextual Distillation Model for Diversified Recommendation—0
Optimal Kernel Orchestration for Tensor Programs with KorchCode1
Decoding the Diversity: A Review of the Indic AI Research Landscape—0
Meta-Learning an Evolvable Developmental EncodingCode0
Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning—0
Pareto Front-Diverse Batch Multi-Objective Bayesian OptimizationCode0
FouRA: Fourier Low Rank Adaptation—0
A Large-scale Universal Evaluation Benchmark For Face Forgery DetectionCode1
Depth Anything V2Code9
Hallo: Hierarchical Audio-Driven Visual Synthesis for Portrait Image AnimationCode9
FairCoT: Enhancing Fairness in Diffusion Models via Chain of Thought Reasoning of Multimodal Language Models—0
SimGen: Simulator-conditioned Driving Scene Generation—0
StableMaterials: Enhancing Diversity in Material Generation via Semi-Supervised Learning—0
MMRel: A Relation Understanding Benchmark in the MLLM EraCode1
Unraveling Code-Mixing Patterns in Migration Discourse: Automated Detection and Analysis of Online Conversations on RedditCode0
Data Augmentation by Fuzzing for Neural Test Generation—0
Dynamic Stochastic Decoding Strategy for Open-Domain Dialogue Generation—0
REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation via Asymptotic EntropyCode1
Multi-Objective Sizing Optimization Method of Microgrid Considering Cost and Carbon Emissions—0
Systematic evaluation of the isolated effect of tissue environment on the transcriptome using a single-cell RNA-seq atlas dataset—0
Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation ModelsCode2
An Optimism-based Approach to Online Evaluation of Generative Models—0
Should XAI Nudge Human Decisions with Explanation Biasing?—0
Beyond the Norms: Detecting Prediction Errors in Regression Models—0
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow UnderstandingCode2
SSCL-IDS: Enhancing Generalization of Intrusion Detection with Self-Supervised Contrastive LearningCode0
Curating Grounded Synthetic Data with Global Perspectives for Equitable AI—0
The Effect of Training Dataset Size on Discriminative and Diffusion-Based Speech Enhancement Systems—0
Learning Continually by Spectral Regularization—0
mHuBERT-147: A Compact Multilingual HuBERT ModelCode0
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark—0
UnSupDLA: Towards Unsupervised Document Layout Analysis—0
Synthesizing Efficient Data with Diffusion Models for Person Re-Identification Pre-TrainingCode1
Data Augmentation in Earth Observation: A Diffusion Model Approach—0
Optimisation of federated learning settings under statistical heterogeneity variations—0
An Efficient Framework for Crediting Data Contributors of Diffusion Models—0
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