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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 5351–5375 of 9051 papers

TitleStatusHype
Majority Vote of Diverse Classifiers for Late Fusion—0
Makadi: A Large-Scale Human-Labeled Dataset for Hindi Semantic Parsing—0
Make a Face: Towards Arbitrary High Fidelity Face Manipulation—0
MAKED: Multi-lingual Automatic Keyword Extraction Dataset—0
Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets—0
Automated Video-EEG Analysis in Epilepsy Studies: Advances and Challenges—0
Make Optimization Once and for All with Fine-grained Guidance—0
Make Templates Smarter: A Template Based Data2Text System Powered by Text Stitch Model—0
Makeup216: Logo Recognition with Adversarial Attention Representations—0
Towards transparency in NLP shared tasks—0
Making Curiosity Explicit in Vision-based RL—0
Dialog State Tracking with Reinforced Data Augmentation—0
Making Sense of Data in the Wild: Data Analysis Automation at Scale—0
Automated test generation to evaluate tool-augmented LLMs as conversational AI agents—0
Making Use of Latent Space in Language GANs for Generating Diverse Text without Pre-training—0
Automated Scoring of Clinical Expressive Language Evaluation Tasks—0
A Conditional Generative Matching Model for Multi-lingual Reply Suggestion—0
MallowsPO: Fine-Tune Your LLM with Preference Dispersions—0
Automated Pruning of Polyculture Plants—0
Automated Generation of Diverse Courses of Actions for Multi-Agent Operations using Binary Optimization and Graph Learning—0
MAML and ANIL Provably Learn Representations—0
Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference—0
Managing Diversity in Airbnb Search—0
Manifold Diffusion Fields—0
Manifold for Machine Learning Assurance—0
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