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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 1351–1400 of 9051 papers

TitleStatusHype
How Do Your Code LLMs Perform? Empowering Code Instruction Tuning with High-Quality DataCode1
Annotation-Efficient Preference Optimization for Language Model AlignmentCode1
Diversified in-domain synthesis with efficient fine-tuning for few-shot classificationCode1
Diversified Batch Selection for Training AccelerationCode1
How Many Topics? Stability Analysis for Topic ModelsCode1
HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMsCode1
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout GenerationCode1
Diversifying Dialog Generation via Adaptive Label SmoothingCode1
HomoFormer: Homogenized Transformer for Image Shadow RemovalCode1
Diversify Your Vision Datasets with Automatic Diffusion-Based AugmentationCode1
ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid MotionsCode1
Diversify Question Generation with Retrieval-Augmented Style TransferCode1
C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot FillingCode1
C^2: Scalable Auto-Feedback for LLM-based Chart GenerationCode1
How Consistent are Clinicians? Evaluating the Predictability of Sepsis Disease Progression with Dynamics ModelsCode1
Online Damage Recovery for Physical Robots with Hierarchical Quality-DiversityCode1
When and how CNNs generalize to out-of-distribution category-viewpoint combinationsCode1
Diversity-aware Channel Pruning for StyleGAN CompressionCode1
Diversity-Aware Meta Visual PromptingCode1
On the effectiveness of task granularity for transfer learningCode1
Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problemCode1
OpenKD: Opening Prompt Diversity for Zero- and Few-shot Keypoint DetectionCode1
Diversity-based Trajectory and Goal Selection with Hindsight Experience ReplayCode1
Calliar: An Online Handwritten Dataset for Arabic CalligraphyCode1
Chain-of-Choice Hierarchical Policy Learning for Conversational RecommendationCode1
Advancing Fine-Grained Classification by Structure and Subject Preserving AugmentationCode1
Diversity-Guided Multi-Objective Bayesian Optimization With Batch EvaluationsCode1
CamContextI2V: Context-aware Controllable Video GenerationCode1
ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative GenerationCode1
Camera-Based Remote Physiology Sensing for Hundreds of Subjects Across Skin TonesCode1
Optimal Counterfactual Explanations for Scorecard modellingCode1
Optimal Kernel Orchestration for Tensor Programs with KorchCode1
GLAMOUR: Graph Learning over Macromolecule RepresentationsCode1
Optimizing Readability Using Genetic AlgorithmsCode1
How Does It Function? Characterizing Long-term Trends in Production Serverless WorkloadsCode1
Diversity-Measurable Anomaly DetectionCode1
Cerbero-7B: A Leap Forward in Language-Specific LLMs Through Enhanced Chat Corpus Generation and EvaluationCode1
CETN: Contrast-enhanced Through Network for CTR PredictionCode1
Overcoming Multi-Model Forgetting in One-Shot NAS With Diversity MaximizationCode1
Generating Progressive Images from Pathological Transitions via Diffusion ModelCode1
DLow: Diversifying Latent Flows for Diverse Human Motion PredictionCode1
Paraphrase Generation as Zero-Shot Multilingual Translation: Disentangling Semantic Similarity from Lexical and Syntactic DiversityCode1
Parea: multi-view ensemble clustering for cancer subtype discoveryCode1
On the effectiveness of partial variance reduction in federated learning with heterogeneous dataCode1
HIPPO: Enhancing the Table Understanding Capability of Large Language Models through Hybrid-Modal Preference OptimizationCode1
Fully Unsupervised Diversity Denoising with Convolutional Variational AutoencodersCode1
HIVE: Evaluating the Human Interpretability of Visual ExplanationsCode1
DLCR: A Generative Data Expansion Framework via Diffusion for Clothes-Changing Person Re-IDCode1
CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich AnnotationsCode1
ConsistencyTTA: Accelerating Diffusion-Based Text-to-Audio Generation with Consistency DistillationCode1
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