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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 851–900 of 9051 papers

TitleStatusHype
Exploring Inter-Channel Correlation for Diversity-Preserved Knowledge DistillationCode1
Design of Chain-of-Thought in Math Problem SolvingCode1
Agree to Disagree: Diversity through Disagreement for Better TransferabilityCode1
Exploring Semantic Consistency and Style Diversity for Domain Generalized Semantic SegmentationCode1
F2GAN: Fusing-and-Filling GAN for Few-shot Image GenerationCode1
Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active ExplorationCode1
Bias Loss for Mobile Neural NetworksCode1
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
Active Learning by Acquiring Contrastive ExamplesCode1
Device-Robust Acoustic Scene Classification via Impulse Response AugmentationCode1
Exploring Design of Multi-Agent LLM Dialogues for Research IdeationCode1
Language-guided Human Motion Synthesis with Atomic ActionsCode1
AbGPT: De Novo Antibody Design via Generative Language ModelingCode1
Beyond Trivial Counterfactual Explanations with Diverse Valuable ExplanationsCode1
DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Diffusion ModelCode1
Addressing the Elephant in the Room: Robust Animal Re-Identification with Unsupervised Part-Based Feature AlignmentCode1
Exploiting Abstract Meaning Representation for Open-Domain Question AnsweringCode1
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and BenchmarkCode1
DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue DatasetCode1
Exploring Effective Data for Surrogate Training Towards Black-Box AttackCode1
DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response GenerationCode1
A single-cell gene expression language modelCode1
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation ExtractionCode1
Difficulty-Aware Simulator for Open Set RecognitionCode1
Explain Me the Painting: Multi-Topic Knowledgeable Art Description GenerationCode1
Beyond Performance Plateaus: A Comprehensive Study on Scalability in Speech EnhancementCode1
Differential Evolution with Reversible Linear TransformationsCode1
Learning Affordance Grounding from Exocentric ImagesCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
Explicit Syntactic Guidance for Neural Text GenerationCode1
Exploring Empty Spaces: Human-in-the-Loop Data AugmentationCode1
DiffSketching: Sketch Control Image Synthesis with Diffusion ModelsCode1
Evolving Flying Machines in Minecraft Using Quality DiversityCode1
Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity RecognitionCode1
exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformer ModelsCode1
DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion modelsCode1
Everyone Deserves A Reward: Learning Customized Human PreferencesCode1
Diffusion for Out-of-Distribution Detection on Road Scenes and BeyondCode1
EvolGAN: Evolutionary Generative Adversarial NetworksCode1
Exclusive Hierarchical Decoding for Deep Keyphrase GenerationCode1
Evaluating Logical Generalization in Graph Neural NetworksCode1
DiffWave: A Versatile Diffusion Model for Audio SynthesisCode1
Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human ProgrammersCode1
Diffusion Reward: Learning Rewards via Conditional Video DiffusionCode1
Evaluating the Evaluation of Diversity in Natural Language GenerationCode1
DirectMultiStep: Direct Route Generation for Multi-Step RetrosynthesisCode1
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity MaximizationCode1
Diversify Your Vision Datasets with Automatic Diffusion-Based AugmentationCode1
Toward a Plug-and-Play Vision-Based Grasping Module for RoboticsCode1
Adding Seemingly Uninformative Labels Helps in Low Data RegimesCode1
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