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Cybersecurity
Digital Marketing
Generative AI
Understanding Medical Research: Your Facebook Friend is Wrong
Algorithms, Part I
Moralities of Everyday Life
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Discover how MemoVis leverages GenAI to revolutionize 3D design feedback through automated companion reference image generation, enhancing visual communication in design workflows.
Explore effective debugging strategies and workflows in Computer-Aided Design through practical insights and methodologies for enhanced problem-solving in CAD environments.
Explore groundbreaking research on electrical muscle stimulation technology integrated into smartwatches, enabling finger movement control through wearable devices.
Explore an innovative natural language interface that revolutionizes ocean science data exploration and analysis through interactive visualization and AI-powered insights.
Explore groundbreaking research on powering full-body wearable devices using intra-body RF energy transmission, advancing the future of wearable technology.
Discover innovative approaches to streamline digital fabrication through specialized 3D scanning techniques and workflows for enhanced manual manufacturing processes.
Explore configurable fairness in recommender systems, focusing on new item recommendations and entry time considerations for enhanced algorithmic equity.
Explore distributionally robust optimization for fair recommendations with limited sensitive attributes in RecSys, enhancing fairness in machine learning applications.
Explore adaptive fair representation learning for personalized fairness in recommendations through information alignment techniques.
Explore techniques for addressing multiple biases in recommender systems, focusing on fairness and accuracy beyond popularity and positivity.
Explore a contextualized and debiased recommender model for fair and accurate recommendations in information retrieval systems.
Explore reinforcement learning-based recommender systems using LLMs for state reward and action modeling in this cutting-edge research presentation.
Explore fair sequential recommendation techniques without relying on user demographics, enhancing ethical AI practices in recommender systems.
Explore data-efficient fine-tuning techniques for LLM-based recommendation systems, enhancing performance with minimal data requirements.
Explore LLM-RecSys alignment through textual ID learning, enhancing recommendation systems with advanced language models.
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