6 citations · 6 across the 2 of their papers we have counts for
3 papers
cs.CV2025
R^2MoE: Redundancy-Removal Mixture of Experts for Lifelong Concept Learning
Xiaohan Guo, Yusong Cai, Zejia Liu +3
Enabling large-scale generative models to continuously learn new visual concepts is essential for personalizing pre-trained models to meet individual user preferences. Existing app…
cs.CL2025
Do Large Language Models know who did what to whom?
Joseph M. Denning, Xiaohan Hannah Guo, Bryor Snefjella +1
Large Language Models (LLMs) are commonly criticized for not understanding language. However, many critiques focus on cognitive abilities that, in humans, are distinct from languag…
cs.CV2021★ 6 cited
CoDeGAN: Contrastive Disentanglement for Generative Adversarial Network
Jiangwei Zhao, Zejia Liu, Xiaohan Guo +1
Disentanglement, a critical concern in interpretable machine learning, has also garnered significant attention from the computer vision community. Many existing GAN-based class dis…