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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 601–625 of 9051 papers

TitleStatusHype
Curiosity-Driven Reinforcement Learning from Human FeedbackCode1
dacl10k: Benchmark for Semantic Bridge Damage SegmentationCode1
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-SpeechCode1
CrowdHuman: A Benchmark for Detecting Human in a CrowdCode1
Cross-Domain Feature Augmentation for Domain GeneralizationCode1
3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D DetectionCode1
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image SteganographyCode1
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised SegmentationCode1
CtrSVDD: A Benchmark Dataset and Baseline Analysis for Controlled Singing Voice Deepfake DetectionCode1
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse LearningCode1
CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context DemonstrationsCode1
COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT ImagesCode1
An End-to-End Multi-Task Learning Model for Image-based Table RecognitionCode1
An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet SpaceCode1
ConZIC: Controllable Zero-shot Image Captioning by Sampling-Based PolishingCode1
Controlling Behavioral Diversity in Multi-Agent Reinforcement LearningCode1
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language ModelsCode1
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet AccuracyCode1
A Closer Look at Machine Unlearning for Large Language ModelsCode1
Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata EcosystemsCode1
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine LearningCode1
Covariance Matrix Adaptation for the Rapid Illumination of Behavior SpaceCode1
Cooperative Open-ended Learning Framework for Zero-shot CoordinationCode1
Cross-Covariate Gait Recognition: A BenchmarkCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
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