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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 2501–2550 of 9051 papers

TitleStatusHype
Channel Self-Supervision for Online Knowledge Distillation—0
Adversarial Training: embedding adversarial perturbations into the parameter space of a neural network to build a robust system—0
A Compressive Memory-based Retrieval Approach for Event Argument Extraction—0
Channel Estimation for MIMO Space Time Coded OTFS under Doubly Selective Channels—0
A Parameterized Family of Meta-Submodular Functions—0
Adversarial Text-to-Image Synthesis: A Review—0
Chameleon Sampling: Diverse and Pure Example Selection for Online Continual Learning with Noisy Labels—0
Chameleon: On the Scene Diversity and Domain Variety of AI-Generated Videos Detection—0
A Paradigm Shift in Mouza Map Vectorization: A Human-Machine Collaboration Approach—0
A Comprehensive Survey on Deep Learning Techniques in Educational Data Mining—0
Domain-wise Adversarial Training for Out-of-Distribution Generalization—0
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation—0
Anywhere: A Multi-Agent Framework for User-Guided, Reliable, and Diverse Foreground-Conditioned Image Generation—0
Challenges in the Knowledge Base Population Slot Filling Task—0
Challenges Encountered in Turkish Natural Language Processing Studies—0
Adversarial Robustness through Dynamic Ensemble Learning—0
Challenges and Strategies in Cross-Cultural NLP—0
Challenges and Solutions in AI for All—0
ChaLearn LAP Large Scale Signer Independent Isolated Sign Language Recognition Challenge: Design, Results and Future Research—0
Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning—0
Do Neural Network Cross-Modal Mappings Really Bridge Modalities?—0
Don't Throw Away Data: Better Sequence Knowledge Distillation—0
Do you MIND? Reflections on the MIND dataset for research on diversity in news recommendations—0
Chain of Functions: A Programmatic Pipeline for Fine-Grained Chart Reasoning Data—0
CG-NeRF: Conditional Generative Neural Radiance Fields—0
AnyHome: Open-Vocabulary Generation of Structured and Textured 3D Homes—0
A Comprehensive Survey of Time Series Forecasting: Architectural Diversity and Open Challenges—0
CFTS-GAN: Continual Few-Shot Teacher Student for Generative Adversarial Networks—0
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds—0
AnyFace: Free-style Text-to-Face Synthesis and Manipulation—0
CFILT IIT Bombay@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion using Multilingual Representation fromTransformers—0
AnyEdit: Mastering Unified High-Quality Image Editing for Any Idea—0
Domain Randomization via Entropy Maximization—0
CET2: Modelling Topic Transitions for Coherent and Engaging Knowledge-Grounded Conversations—0
An upper bound of the mutation probability in the genetic algorithm for general 0-1 knapsack problem—0
An Unsupervised Semantic Sentence Ranking Scheme for Text Documents—0
Adversarial optimization leads to over-optimistic security-constrained dispatch, but sampling can help—0
An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio—0
CDL: Curriculum Dual Learning for Emotion-Controllable Response Generation—0
Deep Single Image Deraining using An Asymetric Cycle Generative and Adversarial Framework—0
A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications—0
7 Tesla multimodal MRI dataset of ex-vivo human brain—0
CCVA-FL: Cross-Client Variations Adaptive Federated Learning for Medical Imaging—0
An Unscented Kalman Filter-Informed Neural Network for Vehicle Sideslip Angle Estimation—0
CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation—0
CAViaR: Context Aware Video Recommendations—0
A Comprehensive Review of Data-Driven Co-Speech Gesture Generation—0
Cause-Aware Empathetic Response Generation via Chain-of-Thought Fine-Tuning—0
Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering—0
Antithetic Noise in Diffusion Models—0
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