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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 3326–3350 of 9051 papers

TitleStatusHype
The #Somos600M Project: Generating NLP resources that represent the diversity of the languages from LATAM, the Caribbean, and Spain—0
Modified CMA-ES Algorithm for Multi-Modal Optimization: Incorporating Niching Strategies and Dynamic Adaptation Mechanism—0
Improving Multilingual Instruction Finetuning via Linguistically Natural and Diverse Datasets—0
Analyzing Persuasive Strategies in Meme Texts: A Fusion of Language Models with Paraphrase Enrichment—0
Iterative Data Generation with Large Language Models for Aspect-based Sentiment Analysis—0
A survey on the impact of AI-based recommenders on human behaviours: methodologies, outcomes and future directions—0
The Factuality Tax of Diversity-Intervened Text-to-Image Generation: Benchmark and Fact-Augmented InterventionCode0
Multi-task multi-constraint differential evolution with elite-guided knowledge transfer for coal mine integrated energy system dispatching—0
Deep Reinforcement Learning Strategies in Finance: Insights into Asset Holding, Trading Behavior, and Purchase Diversity—0
From Local Concepts to Universals: Evaluating the Multicultural Understanding of Vision-Language Models—0
CMMaTH: A Chinese Multi-modal Math Skill Evaluation Benchmark for Foundation Models—0
Paraphrase Types Elicit Prompt Engineering CapabilitiesCode0
Surrogate-assisted evolutionary framework with an ensemble of teaching-learning and differential evolution for expensive optimizationCode0
Doc2Token: Bridging Vocabulary Gap by Predicting Missing Tokens for E-commerce Search—0
Optimizing Cyber Defense in Dynamic Active Directories through Reinforcement Learning—0
Detection and Measurement of Syntactic Templates in Generated Text—0
Debate-to-Write: A Persona-Driven Multi-Agent Framework for Diverse Argument GenerationCode0
Factor-Conditioned Speaking-Style Captioning—0
OTFS-NOMA System for MIMO Communication Networks with Spatial Diversity—0
Manipulate-Anything: Automating Real-World Robots using Vision-Language Models—0
Are Generative Language Models Multicultural? A Study on Hausa Culture and Emotions using ChatGPT—0
EmPO: Emotion Grounding for Empathetic Response Generation through Preference OptimizationCode0
The Great AI Witch Hunt: Reviewers Perception and (Mis)Conception of Generative AI in Research Writing—0
Inclusivity in Large Language Models: Personality Traits and Gender Bias in Scientific Abstracts—0
Data Generation Using Large Language Models for Text Classification: An Empirical Case Study—0
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