849 citations · 1.1k across the 19 of their papers we have counts for
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cs.LG2023★ 20 cited
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs
Zhikai Chen, Haitao Mao, Hang Li +8
Learning on Graphs has attracted immense attention due to its wide real-world applications. The most popular pipeline for learning on graphs with textual node attributes primarily…
cs.LG2023★ 9 cited
Generative Diffusion Models on Graphs: Methods and Applications
Chengyi Liu, Wenqi Fan, Yunqing Liu +5
Diffusion models, as a novel generative paradigm, have achieved remarkable success in various image generation tasks such as image inpainting, image-to-text translation, and video…
cs.CV2023
Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks
Xinsong Zhang, Yan Zeng, Jipeng Zhang +1
Foundation models or pre-trained models have substantially improved the performance of various language, vision, and vision-language understanding tasks. However, existing foundati…