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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 1351–1375 of 9051 papers

TitleStatusHype
Bench4Merge: A Comprehensive Benchmark for Merging in Realistic Dense Traffic with Micro-Interactive VehiclesCode0
Tighter Performance Theory of FedExProx—0
LAC: Graph Contrastive Learning with Learnable Augmentation in Continuous Space—0
Synthetic Data Generation for Residential Load Patterns via Recurrent GAN and Ensemble Method—0
Who is Undercover? Guiding LLMs to Explore Multi-Perspective Team Tactic in the Game—0
On the Diversity of Synthetic Data and its Impact on Training Large Language Models—0
CAST: Corpus-Aware Self-similarity Enhanced Topic modelling—0
An Electoral Approach to Diversify LLM-based Multi-Agent Collective Decision-MakingCode0
mHumanEval -- A Multilingual Benchmark to Evaluate Large Language Models for Code GenerationCode0
Theoretical Aspects of Bias and Diversity in Minimum Bayes Risk DecodingCode0
LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model—0
GDPO: Learning to Directly Align Language Models with Diversity Using GFlowNets—0
Distribution-Aware Compensation Design for Sustainable Data Rights in Machine Learning—0
SYNOSIS: Image synthesis pipeline for machine vision in metal surface inspection—0
Compression using Discrete Multi-Level Divisor Transform for Heterogeneous Sensor Data—0
MetaAlign: Align Large Language Models with Diverse Preferences during Inference TimeCode0
DFlow: Diverse Dialogue Flow Simulation with Large Language Models—0
Measuring Diversity: Axioms and Challenges—0
Soft-Label Integration for Robust Toxicity ClassificationCode0
LEAD: Latent Realignment for Human Motion Diffusion—0
Nova: An Iterative Planning and Search Approach to Enhance Novelty and Diversity of LLM Generated Ideas—0
How Does Data Diversity Shape the Weight Landscape of Neural Networks?—0
SwaQuAD-24: QA Benchmark Dataset in Swahili—0
CFTS-GAN: Continual Few-Shot Teacher Student for Generative Adversarial Networks—0
FaceSaliencyAug: Mitigating Geographic, Gender and Stereotypical Biases via Saliency-Based Data Augmentation—0
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