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
An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering
Zaber Al Hassan Ayon, Gulam Husain, Roshankumar Bisoi, Waliur Rahman, Dr Tom Osborn
Generative AI in Education: From Foundational Insights to the Socratic Playground for Learning
Xiangen Hu, Sheng Xu, Richard Tong, Art Graesser
EmoXpt: Analyzing Emotional Variances in Human Comments and LLM-Generated Responses
Shireesh Reddy Pyreddy, Tarannum Shaila Zaman
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement Learning
Stella C. Dong, James R. Finlay
Has an AI model been trained on your images?
Matyas Bohacek, Hany Farid
Ultrasound Image Synthesis Using Generative AI for Lung Ultrasound Detection
Yu-Cheng Chou, Gary Y. Li, Li Chen, Mohsen Zahiri, Naveen Balaraju, Shubham Patil, Bryson Hicks, Nikolai Schnittke, David O. Kessler, Jeffrey Shupp, Maria Parker, Cristiana Baloescu, Christopher Moore, Cynthia Gregory, Kenton Gregory, Balasundar Raju, Jochen Kruecker, Alvin Chen
Environmental large language model Evaluation (ELLE) dataset: A Benchmark for Evaluating Generative AI applications in Eco-environment Domain
Jing Guo, Nan Li, Ming Xu
Generative AI for Cel-Animation: A Survey
Yunlong Tang, Junjia Guo, Pinxin Liu, Zhiyuan Wang, Hang Hua, Jia-Xing Zhong, Yunzhong Xiao, Chao Huang, Luchuan Song, Susan Liang, Yizhi Song, Liu He, Jing Bi, Mingqian Feng, Xinyang Li, Zeliang Zhang, Chenliang Xu
Video Summarisation with Incident and Context Information using Generative AI
Ulindu De Silva, Leon Fernando, Kalinga Bandara, Rashmika Nawaratne
The Future of AI: Exploring the Potential of Large Concept Models
Hussain Ahmad, Diksha Goel
A Statistical Theory of Contrastive Pre-training and Multimodal Generative AI
Kazusato Oko, Licong Lin, Yuhang Cai, Song Mei
Knowledge Retrieval Based on Generative AI
Te-Lun Yang, Jyi-Shane Liu, Yuen-Hsien Tseng, Jyh-Shing Roger Jang
User Simulation in the Era of Generative AI: User Modeling, Synthetic Data Generation, and System Evaluation
Krisztian Balog, ChengXiang Zhai