Large Language Model
FiV A: Fine-grained Visual Attribute Dataset for Text-to-Image Diffusion Models Tong Wu
Recent advances in text-to-image generation have enabled the creation of high-quality images with diverse applications.
Learning Multimodal LLMs without Text-only Forgetting
The LoRRA mirrors the structure of attention but utilizes low-rank connections to ensure efficiency. Initially, image and text inputs are aligned with visual learners operating alongside the main attention, balancing focus on visual elements.
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs) Jerry Y ao-Chieh Hu Weimin Wu Zhuoru Li Sophia Pi Zhao Song Han Liu
We investigate the statistical and computational limits of latent diffusion transformers (DiTs), assuming the data is supported on an unknown low-dimensional linear subspace.
Estimating the Hallucination Rate of Generative AI Andrew Jesson Nicolas Beltran-V elez * Quentin Chu
In ICL, a conditional generative model (CGM) is prompted with a dataset and a prediction question and asked to generate a response.