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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 2626–2650 of 9051 papers

TitleStatusHype
An Analysis of the Preferences of Distribution Indicators in Evolutionary Multi-Objective Optimization—0
Protected group bias and stereotypes in Large Language Models—0
Improving the Robustness of Large Language Models via Consistency Alignment—0
A reinforcement learning guided hybrid evolutionary algorithm for the latency location routing problemCode0
LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion ModelsCode0
Protein Conformation Generation via Force-Guided SE(3) Diffusion ModelsCode2
EDT: Improving Large Language Models' Generation by Entropy-based Dynamic Temperature Sampling—0
M^3AV: A Multimodal, Multigenre, and Multipurpose Audio-Visual Academic Lecture Dataset—0
EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation—0
The Bid Picture: Auction-Inspired Multi-player Generative Adversarial Networks Training—0
Enhancing Fingerprint Image Synthesis with GANs, Diffusion Models, and Style Transfer Techniques—0
Technical Report: Competition Solution For BetterMixture—0
Diversity-aware Channel Pruning for StyleGAN CompressionCode1
Learning Coherent Matrixized Representation in Latent Space for Volumetric 4D Generation—0
IDAdapter: Learning Mixed Features for Tuning-Free Personalization of Text-to-Image Models—0
Progressive trajectory matching for medical dataset distillation—0
On Pretraining Data Diversity for Self-Supervised LearningCode1
Wav2Gloss: Generating Interlinear Glossed Text from SpeechCode0
Diversity-Aware Agnostic Ensemble of Sharpness Minimizers—0
Planner3D: LLM-enhanced graph prior meets 3D indoor scene explicit regularization—0
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial TrajectoryCode1
DreamDA: Generative Data Augmentation with Diffusion ModelsCode1
Controllable Face Synthesis with Semantic Latent Diffusion ModelsCode1
Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal DataCode0
Deciphering AutoML Ensembles: cattleia's Assistance in Decision-Making—0
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