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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 3151–3200 of 9051 papers

TitleStatusHype
Toward Improving Robustness of Object Detectors Against Domain ShiftCode1
AAMDM: Accelerated Auto-regressive Motion Diffusion Model—0
Combining Kernelized Autoencoding and Centroid Prediction for Dynamic Multi-objective Optimization—0
Dynamic Inertial Poser (DynaIP): Part-Based Motion Dynamics Learning for Enhanced Human Pose Estimation with Sparse Inertial SensorsCode1
DiverseDream: Diverse Text-to-3D Synthesis with Augmented Text Embedding—0
Beyond Accuracy: Statistical Measures and Benchmark for Evaluation of Representation from Self-Supervised Learning—0
Biased Random-Key Genetic Algorithms: A Review—0
Improving Unsupervised Relation Extraction by Augmenting Diverse Sentence PairsCode0
Sequential Modeling Enables Scalable Learning for Large Vision ModelsCode3
LLM-TAKE: Theme Aware Keyword Extraction Using Large Language Models—0
3DiFACE: Diffusion-based Speech-driven 3D Facial Animation and Editing—0
Generative artificial intelligence enhances creativity but reduces the diversity of novel content—0
Meta-Diversity Search in Complex Systems, A Recipe for Artificial Open-Endedness ?—0
Improving the Robustness of Quantized Deep Neural Networks to White-Box Attacks using Stochastic Quantization and Information-Theoretic Ensemble Training—0
Perturbation-based Effect Measures for Compositional DataCode0
OmniMotionGPT: Animal Motion Generation with Limited Data—0
Few-shot Image Generation via Style Adaptation and Content Preservation—0
Prompt-Based Exemplar Super-Compression and Regeneration for Class-Incremental LearningCode0
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component AnalysisCode0
COVIDx CXR-4: An Expanded Multi-Institutional Open-Source Benchmark Dataset for Chest X-ray Image-Based Computer-Aided COVID-19 Diagnostics—0
W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised CalibrationCode1
Continual Learning for Image Segmentation with Dynamic QueryCode1
Spectral and Polarization Vision: Spectro-polarimetric Real-world Dataset—0
Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language ModelCode3
DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Diffusion ModelCode1
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion SegmentationCode1
Scene Summarization: Clustering Scene Videos into Spatially Diverse Frames—0
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play—0
Large Language Models Suffer From Their Own Output: An Analysis of the Self-Consuming Training Loop—0
StyleCap: Automatic Speaking-Style Captioning from Speech Based on Speech and Language Self-supervised Learning Models—0
TextDiffuser-2: Unleashing the Power of Language Models for Text Rendering—0
The curse of language biases in remote sensing VQA: the role of spatial attributes, language diversity, and the need for clear evaluation—0
HD Maps are Lane Detection Generalizers: A Novel Generative Framework for Single-Source Domain Generalization—0
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models—0
Spatial Diarization for Meeting Transcription with Ad-Hoc Acoustic Sensor NetworksCode0
Exploring Attribute Variations in Style-based GANs using Diffusion Models—0
Metric Space Magnitude for Evaluating the Diversity of Latent RepresentationsCode1
Reinforcement Learning from Diffusion Feedback: Q* for Image Search—0
Efficient Dataset Distillation via Minimax DiffusionCode1
Cerbero-7B: A Leap Forward in Language-Specific LLMs Through Enhanced Chat Corpus Generation and EvaluationCode1
GAIA: Zero-shot Talking Avatar Generation—0
Vector-Quantized Prompt Learning for Paraphrase Generation—0
A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography—0
RandMSAugment: A Mixed-Sample Augmentation for Limited-Data Scenarios—0
CUCL: Codebook for Unsupervised Continual LearningCode0
Fine-Grained Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation—0
Mitigating Shortcut Learning with Diffusion Counterfactuals and Diverse Ensembles—0
Enhancing Task-Oriented Dialogues with Chitchat: a Comparative Study Based on Lexical Diversity and DivergenceCode0
Dialogue Quality and Emotion Annotations for Customer Support ConversationsCode0
Grammatical Error Correction via Mixed-Grained Weighted Training—0
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