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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 551–575 of 9051 papers

TitleStatusHype
DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning GraphCode1
Data Augmentation using Pre-trained Transformer ModelsCode1
Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based RecommendationCode1
dacl10k: Benchmark for Semantic Bridge Damage SegmentationCode1
D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data PruningCode1
Curriculum-guided Hindsight Experience ReplayCode1
Curiosity-Driven Reinforcement Learning from Human FeedbackCode1
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic ModelsCode1
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-SpeechCode1
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised SegmentationCode1
CrowdHuman: A Benchmark for Detecting Human in a CrowdCode1
ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative GenerationCode1
Advancing Fine-Grained Classification by Structure and Subject Preserving AugmentationCode1
An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet SpaceCode1
CtrSVDD: A Benchmark Dataset and Baseline Analysis for Controlled Singing Voice Deepfake DetectionCode1
DALDA: Data Augmentation Leveraging Diffusion Model and LLM with Adaptive Guidance ScalingCode1
CreoPep: A Universal Deep Learning Framework for Target-Specific Peptide Design and OptimizationCode1
Cross-Covariate Gait Recognition: A BenchmarkCode1
COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse LearningCode1
COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT ImagesCode1
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image SteganographyCode1
CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context DemonstrationsCode1
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
An End-to-End Multi-Task Learning Model for Image-based Table RecognitionCode1
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