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
How Novice Programmers Use and Experience ChatGPT when Solving Programming Exercises in an Introductory Course
Andreas Scholl, Natalie Kiesler
SceneTeller: Language-to-3D Scene Generation
Başak Melis Öcal, Maxim Tatarchenko, Sezer Karaoglu, Theo Gevers
CultureVo: The Serious Game of Utilizing Gen AI for Enhancing Cultural Intelligence
Ajita Agarwala, Anupam Purwar, Viswanadhasai Rao
Machine Unlearning in Generative AI: A Survey
Zheyuan Liu, Guangyao Dou, Zhaoxuan Tan, Yijun Tian, Meng Jiang
Generative AI like ChatGPT in Blockchain Federated Learning: use cases, opportunities and future
Sai Puppala, Ismail Hossain, Md Jahangir Alam, Sajedul Talukder, Jannatul Ferdaus, Mahedi Hasan, Sameera Pisupati, Shanmukh Mathukumilli
Combining Cognitive and Generative AI for Self-explanation in Interactive AI Agents
Shalini Sushri, Rahul Dass, Rhea Basappa, Hong Lu, Ashok Goel
Revolutionizing Undergraduate Learning: CourseGPT and Its Generative AI Advancements
Ahmad M. Nazar, Mohamed Y. Selim, Ashraf Gaffar, Shakil Ahmed
Building a Domain-specific Guardrail Model in Production
Mohammad Niknazar, Paul V Haley, Latha Ramanan, Sang T. Truong, Yedendra Shrinivasan, Ayan Kumar Bhowmick, Prasenjit Dey, Ashish Jagmohan, Hema Maheshwari, Shom Ponoth, Robert Smith, Aditya Vempaty, Nick Haber, Sanmi Koyejo, Sharad Sundararajan
A Survey Forest Diagram : Gain a Divergent Insight View on a Specific Research Topic
Jinghong Li, Wen Gu, Koichi Ota, Shinobu Hasegawa
Generative artificial intelligence in dentistry: Current approaches and future challenges
Fabián Villena, Claudia Véliz, Rosario García-Huidobro, Sebastián Aguayo