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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

Showing 13011325 of 9051 papers

TitleStatusHype
Merging and Splitting Diffusion Paths for Semantically Coherent PanoramasCode1
AutoMix: Automatically Mixing Language ModelsCode1
Difficulty-Aware Simulator for Open Set RecognitionCode1
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Automating Rigid Origami DesignCode1
Diff-Mosaic: Augmenting Realistic Representations in Infrared Small Target Detection via Diffusion PriorCode1
Graph Meta Network for Multi-Behavior RecommendationCode1
Diversity is Definitely Needed: Improving Model-Agnostic Zero-shot Classification via Stable DiffusionCode1
Griffin: Towards a Graph-Centric Relational Database Foundation ModelCode1
BoostTree and BoostForest for Ensemble LearningCode1
GUARD: A Safe Reinforcement Learning BenchmarkCode1
HIPPO: Enhancing the Table Understanding Capability of Large Language Models through Hybrid-Modal Preference OptimizationCode1
Bootstrapping Referring Multi-Object TrackingCode1
CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation FrameworkCode1
CAPIVARA: Cost-Efficient Approach for Improving Multilingual CLIP Performance on Low-Resource LanguagesCode1
Global Tensor Motion PlanningCode1
Can we use Common Voice to train a Multi-Speaker TTS system?Code1
Global Adaptation meets Local Generalization: Unsupervised Domain Adaptation for 3D Human Pose EstimationCode1
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive TestingCode1
Can pre-trained models assist in dataset distillation?Code1
DiffuSum: Generation Enhanced Extractive Summarization with DiffusionCode1
DiffWave: A Versatile Diffusion Model for Audio SynthesisCode1
Advanced Codebook Design for SCMA-aided NTNs With Randomly Distributed UsersCode1
Mitigating Gender Bias for Neural Dialogue Generation with Adversarial LearningCode1
Towards Geospatial Foundation Models via Continual PretrainingCode1
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