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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 476–500 of 9051 papers

TitleStatusHype
Recover from Horcrux: A Spectrogram Augmentation Method for Cardiac Feature Monitoring from Radar Signal Components—0
VisualQuest: A Diverse Image Dataset for Evaluating Visual Recognition in LLMs—0
Evaluating Bias in LLMs for Job-Resume Matching: Gender, Race, and Education—0
Evolutionary Policy Optimization—0
Enhancing Symbolic Regression with Quality-Diversity and Physics-Inspired ConstraintsCode0
Information-Seeking Decision Strategies Mitigate Risk in Dynamic, Uncertain EnvironmentsCode0
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-TrainingCode1
Advancing Cross-Organ Domain Generalization with Test-Time Style Transfer and Diversity Enhancement—0
Generative Dataset Distillation using Min-Max Diffusion Model—0
Tuning-Free Amodal Segmentation via the Occlusion-Free Bias of Inpainting Models—0
Parental Guidance: Efficient Lifelong Learning through Evolutionary Distillation—0
Unraveling the Effects of Synthetic Data on End-to-End Autonomous DrivingCode1
Unseen from Seen: Rewriting Observation-Instruction Using Foundation Models for Augmenting Vision-Language NavigationCode1
good4cir: Generating Detailed Synthetic Captions for Composed Image Retrieval—0
Visual Variational Autoencoder Prompt Tuning—0
TreeSynth: Synthesizing Diverse Data from Scratch via Tree-Guided Subspace Partitioning—0
DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology DiagnosisCode0
When Debate Fails: Bias Reinforcement in Large Language Models—0
Preference-Guided Diffusion for Multi-Objective Offline Optimization—0
Modifying Large Language Model Post-Training for Diverse Creative WritingCode2
Align Your Rhythm: Generating Highly Aligned Dance Poses with Gating-Enhanced Rhythm-Aware Feature Representation—0
Dereflection Any Image with Diffusion Priors and Diversified DataCode2
ARFlow: Human Action-Reaction Flow Matching with Physical Guidance—0
Whenever, Wherever: Towards Orchestrating Crowd Simulations with Spatio-Temporal Spawn DynamicsCode0
CAARMA: Class Augmentation with Adversarial Mixup Regularization—0
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