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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 1626–1650 of 9051 papers

TitleStatusHype
Privacy-Preserving Federated Learning with Consistency via Knowledge Distillation Using Conditional Generator—0
A Novel Mathematical Framework for Objective Characterization of Ideas—0
When More Data Hurts: Optimizing Data Coverage While Mitigating Diversity Induced Underfitting in an Ultra-Fast Machine-Learned Potential—0
DiffTED: One-shot Audio-driven TED Talk Video Generation with Diffusion-based Co-speech Gestures—0
Data Augmentation via Latent Diffusion for Saliency PredictionCode1
Diversity-Driven View Subset Selection for Indoor Novel View SynthesisCode0
MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model—0
Table-to-Text Generation with Pretrained Diffusion Models—0
Human Motion Synthesis_ A Diffusion Approach for Motion Stitching and In-Betweening—0
HybridFC: A Hybrid Fact-Checking Approach for Knowledge GraphsCode0
Automated Data Augmentation for Few-Shot Time Series Forecasting: A Reinforcement Learning Approach Guided by a Model Zoo—0
Advancing Topic Segmentation of Broadcasted Speech with Multilingual Semantic EmbeddingsCode0
AbGPT: De Novo Antibody Design via Generative Language ModelingCode1
DiffusionPen: Towards Controlling the Style of Handwritten Text GenerationCode2
UPCS: Unbiased Persona Construction for Dialogue Generation—0
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct—0
UAVDB: Trajectory-Guided Adaptable Bounding Boxes for UAV DetectionCode1
Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models—0
Prim2Room: Layout-Controllable Room Mesh Generation from Primitives—0
Seeing is Believing? Enhancing Vision-Language Navigation using Visual Perturbations—0
LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-Layer Optical Flow—0
Prototype-Driven Multi-Feature Generation for Visible-Infrared Person Re-identificationCode1
Distribution Discrepancy and Feature Heterogeneity for Active 3D Object DetectionCode0
Algorithmic Scenario Generation as Quality Diversity Optimization—0
Leveraging LLMs for Influence Path Planning in Proactive Recommendation—0
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