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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 3026–3050 of 9051 papers

TitleStatusHype
ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)—0
When More Data Hurts: Optimizing Data Coverage While Mitigating Diversity Induced Underfitting in an Ultra-Fast Machine-Learned Potential—0
Diversity-Driven View Subset Selection for Indoor Novel View SynthesisCode0
DiffTED: One-shot Audio-driven TED Talk Video Generation with Diffusion-based Co-speech Gestures—0
MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model—0
HybridFC: A Hybrid Fact-Checking Approach for Knowledge GraphsCode0
Advancing Topic Segmentation of Broadcasted Speech with Multilingual Semantic EmbeddingsCode0
Automated Data Augmentation for Few-Shot Time Series Forecasting: A Reinforcement Learning Approach Guided by a Model Zoo—0
Table-to-Text Generation with Pretrained Diffusion Models—0
Human Motion Synthesis_ A Diffusion Approach for Motion Stitching and In-Betweening—0
Prim2Room: Layout-Controllable Room Mesh Generation from Primitives—0
UPCS: Unbiased Persona Construction for Dialogue Generation—0
Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models—0
LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-Layer Optical Flow—0
Seeing is Believing? Enhancing Vision-Language Navigation using Visual Perturbations—0
Distribution Discrepancy and Feature Heterogeneity for Active 3D Object DetectionCode0
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct—0
Algorithmic Scenario Generation as Quality Diversity Optimization—0
Fine-Grained Representation Learning via Multi-Level Contrastive Learning without Class PriorsCode0
Leveraging LLMs for Influence Path Planning in Proactive Recommendation—0
Open Language Data Initiative: Advancing Low-Resource Machine Translation for Karakalpak—0
D4: Text-guided diffusion model-based domain adaptive data augmentation for vineyard shoot detection—0
Multi-Modal Diffusion for Hand-Object Grasp GenerationCode0
Absolute Ranking: An Essential Normalization for Benchmarking Optimization Algorithms—0
A high-accuracy multi-model mixing retrosynthetic method—0
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