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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 2051–2075 of 9051 papers

TitleStatusHype
DivCon-NeRF: Generating Augmented Rays with Diversity and Consistency for Few-shot View Synthesis—0
BlobCtrl: A Unified and Flexible Framework for Element-level Image Generation and Editing—0
KVShare: An LLM Service System with Efficient and Effective Multi-Tenant KV Cache Reuse—0
Personalize Anything for Free with Diffusion Transformer—0
Tailor: An Integrated Text-Driven CG-Ready Human and Garment Generation System—0
D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning—0
Make Optimization Once and for All with Fine-grained Guidance—0
Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models—0
MUSS: Multilevel Subset Selection for Relevance and Diversity—0
Beamforming for Movable and Rotatable Antenna Enabled Multi-User Communications—0
RONA: Pragmatically Diverse Image Captioning with Coherence RelationsCode0
FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAGCode0
Information Density Principle for MLLM BenchmarksCode0
Distilling Diversity and Control in Diffusion Models—0
Climate land use and other drivers impacts on island ecosystem services: a global review—0
Channel-wise Noise Scheduled Diffusion for Inverse Rendering in Indoor Scenes—0
Streaming Generation of Co-Speech Gestures via Accelerated Rolling Diffusion—0
Ordered Semantically Diverse Sampling for Textual Data—0
DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse TasksCode0
Monte Carlo Diffusion for Generalizable Learning-Based RANSAC—0
Considering Length Diversity in Retrieval-Augmented SummarizationCode0
Leveraging Semantic Attribute Binding for Free-Lunch Color Control in Diffusion Models—0
Maintaining diversity in structured populationsCode0
SCOPE-DTI: Semi-Inductive Dataset Construction and Framework Optimization for Practical Usability Enhancement in Deep Learning-Based Drug Target Interaction PredictionCode0
Proceedings of the ISCA/ITG Workshop on Diversity in Large Speech and Language Models—0
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