40 citations · 41 across the 7 of their papers we have counts for
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cs.LG2024★ 1 cited
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…
cs.LG2024
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…
cs.LG2024★ 40 cited
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…