40 citations · 41 across the 7 of their papers we have counts for
4 papers · 1 filter
LatentExplainer: Explaining Latent Representations in Deep Generative Models with Multimodal Large Language Models
Mengdan Zhu, Raasikh Kanjiani, Jiahui Lu +3
Deep generative models like VAEs and diffusion models have advanced various generation tasks by leveraging latent variables to learn data distributions and generate high-quality sa…
DUE: Dynamic Uncertainty-Aware Explanation Supervision via 3D Imputation
Qilong Zhao, Yifei Zhang, Mengdan Zhu +4
Explanation supervision aims to enhance deep learning models by integrating additional signals to guide the generation of model explanations, showcasing notable improvements in bot…
Explaining latent representations of generative models with large multimodal models
Mengdan Zhu, Zhenke Liu, Bo Pan +2
Learning interpretable representations of data generative latent factors is an important topic for the development of artificial intelligence. With the rise of the large multimodal…
Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models
Guangji Bai, Zheng Chai, Chen Ling +11
The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI's ChatGPT, represents a significant advancement in artificial intelligence. Th…