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
Free to play: UN Trade and Development's experience with developing its own open-source Retrieval Augmented Generation Large Language Model application
Daniel Hopp
Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine
Rui Yang, Yilin Ning, Emilia Keppo, Mingxuan Liu, Chuan Hong, Danielle S Bitterman, Jasmine Chiat Ling Ong, Daniel Shu Wei Ting, Nan Liu
Generative Artificial Intelligence-Guided User Studies: An Application for Air Taxi Services
Shengdi Xiao, Jingjing Li, Tatsuki Fushimi, Yoichi Ochiai
CELL your Model: Contrastive Explanations for Large Language Models
Ronny Luss, Erik Miehling, Amit Dhurandhar
HoLLMwood: Unleashing the Creativity of Large Language Models in Screenwriting via Role Playing
Jing Chen, Xinyu Zhu, Cheng Yang, Chufan Shi, Yadong Xi, Yuxiang Zhang, Junjie Wang, Jiashu Pu, Rongsheng Zhang, Yujiu Yang, Tian Feng
ChildDiffusion: Unlocking the Potential of Generative AI and Controllable Augmentations for Child Facial Data using Stable Diffusion and Large Language Models
Muhammad Ali Farooq, Wang Yao, Peter Corcoran
Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classification
Martin Juan José Bucher, Marco Martini
Tailoring Generative AI Chatbots for Multiethnic Communities in Disaster Preparedness Communication: Extending the CASA Paradigm
Xinyan Zhao, Yuan Sun, Wenlin Liu, Chau-Wai Wong
Estimating the Hallucination Rate of Generative AI
Andrew Jesson, Nicolas Beltran-Velez, Quentin Chu, Sweta Karlekar, Jannik Kossen, Yarin Gal, John P. Cunningham, David Blei
Evaluating Contextually Personalized Programming Exercises Created with Generative AI
Evanfiya Logacheva, Arto Hellas, James Prather, Sami Sarsa, Juho Leinonen
What's in an embedding? Would a rose by any embedding smell as sweet?
Venkat Venkatasubramanian
Survey for Landing Generative AI in Social and E-commerce Recsys -- the Industry Perspectives
Da Xu, Danqing Zhang, Guangyu Yang, Bo Yang, Shuyuan Xu, Lingling Zheng, Cindy Liang
Deep Generative Modeling Reshapes Compression and Transmission: From Efficiency to Resiliency
Jincheng Dai, Xiaoqi Qin, Sixian Wang, Lexi Xu, Kai Niu, Ping Zhang
Re.Dis.Cover Place with Generative AI: Exploring the Experience and Design of City Wandering with Image-to-Image AI
Peng-Kai Hung, Janet Yi-Ching Huang, Stephan Wensveen, Rung-Huei Liang