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.
675papers
Papers - Page 28
June 11, 2024
June 10, 2024
Survey for Landing Generative AI in Social and E-commerce Recsys -- the Industry Perspectives
Deep Generative Modeling Reshapes Compression and Transmission: From Efficiency to Resiliency
Re.Dis.Cover Place with Generative AI: Exploring the Experience and Design of City Wandering with Image-to-Image AI
Latent Directions: A Simple Pathway to Bias Mitigation in Generative AI
Towards Signal Processing In Large Language Models
June 9, 2024
June 7, 2024
How to Strategize Human Content Creation in the Era of GenAI?
LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models
Generative AI Models: Opportunities and Risks for Industry and Authorities
Morescient GAI for Software Engineering (Extended Version)
Evaluating and Mitigating IP Infringement in Visual Generative AI
June 6, 2024