Generative AI
Generative AI focuses on creating new content, ranging from text and images to code and even simulations of complex systems like fluid flows, primarily using large language models (LLMs) and generative adversarial networks (GANs). Current research emphasizes improving model accuracy, addressing biases and ethical concerns, and exploring effective human-AI collaboration in diverse applications like education, healthcare, and software development. This rapidly evolving field holds significant potential to accelerate scientific discovery and transform various industries by automating tasks, generating insights from large datasets, and personalizing services.
Papers
Intelligent Canvas: Enabling Design-Like Exploratory Visual Data Analysis with Generative AI through Rapid Prototyping, Iteration and Curation
Zijian Ding, Joel Chan
Rethinking Machine Unlearning for Large Language Models
Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu
A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation
Xiangru Tang, Howard Dai, Elizabeth Knight, Fang Wu, Yunyang Li, Tianxiao Li, Mark Gerstein
Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot
Ionut Daniel Fagadau, Leonardo Mariani, Daniela Micucci, Oliviero Riganelli
Mapping the Ethics of Generative AI: A Comprehensive Scoping Review
Thilo Hagendorff
Enhancing Programming Error Messages in Real Time with Generative AI
Bailey Kimmel, Austin Geisert, Lily Yaro, Brendan Gipson, Taylor Hotchkiss, Sidney Osae-Asante, Hunter Vaught, Grant Wininger, Chase Yamaguchi
Tailoring Education with GenAI: A New Horizon in Lesson Planning
Kostas Karpouzis, Dimitris Pantazatos, Joanna Taouki, Kalliopi Meli
Bringing Generative AI to Adaptive Learning in Education
Hang Li, Tianlong Xu, Chaoli Zhang, Eason Chen, Jing Liang, Xing Fan, Haoyang Li, Jiliang Tang, Qingsong Wen
Generative AI for Education (GAIED): Advances, Opportunities, and Challenges
Paul Denny, Sumit Gulwani, Neil T. Heffernan, Tanja Käser, Steven Moore, Anna N. Rafferty, Adish Singla
How Can Generative AI Enhance the Well-being of Blind?
Oliver Bendel
At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligence
Abdulkadir Celik, Ahmed M. Eltawil
Chameleon: Foundation Models for Fairness-aware Multi-modal Data Augmentation to Enhance Coverage of Minorities
Mahdi Erfanian, H. V. Jagadish, Abolfazl Asudeh