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Graph-structured data are the commonly used and have wide application scenarios in the real world.
Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2016
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl · 2017
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Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne Van Den Berg, Ivan Titov, and Max Welling · 2018
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Taking human out of learning applications: A survey on automated machine learning
Quanming Yao, Mengshuo Wang, Yuqiang Chen, Wenyuan Dai, Yu-Feng Li, Wei-Wei Tu, Qiang Yang, and Yang Yu · 2018
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 2019
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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Design space for graph neural networks
Jiaxuan You, Zhitao Ying, and Jure Leskovec · 2020
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Automated machine learning on graphs: A survey
Ziwei Zhang, Xin Wang, and Wenwu Zhu · 2021
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Taxonomy of benchmarks in graph representation learning
Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O’Bray, Michael Perlmutter, Bastian Rieck, Matthew Hirn, et al · 2022
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Transformer for graphs: An overview from architecture perspective
Erxue Min, Runfa Chen, Yatao Bian, Tingyang Xu, Kangfei Zhao, Wenbing Huang, Peilin Zhao, Junzhou Huang, Sophia Ananiadou, and Yu Rong · 2022
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Gppt: Graph pre-training and prompt tuning to generalize graph neural networks
Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, and Xin Wang · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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Efficient hyper-parameter search for knowledge graph embedding
Yongqi Zhang, Zhanke Zhou, Quanming Yao, and Yong Li · 2022
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Graphllm: Boosting graph reasoning ability of large language model
Ziwei Chai, Tianjie Zhang, Liang Wu, Kaiqiao Han, Xiaohai Hu, Xuanwen Huang, and Yang Yang · 2023
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Autokg: Efficient automated knowledge graph generation for language models
Bohan Chen and Andrea L Bertozzi · 2023
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Exploring the potential of large language models (llms) in learning on graphs
Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, et al · 2023
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2023
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Talk like a graph: Encoding graphs for large language models
Bahare Fatemi, Jonathan Halcrow, and Bryan Perozzi · 2023
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Gaia: a benchmark for general ai assistants
Grégoire Mialon, Clémentine Fourrier, Craig Swift, Thomas Wolf, Yann LeCun, and Thomas Scialom · 2023
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Can large language models empower molecular property prediction?
Chen Qian, Huayi Tang, Zhirui Yang, Hong Liang, and Yong Liu · 2023
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Hugginggpt: Solving ai tasks with chatgpt and its friends in huggingface
Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, and Yueting Zhuang · 2023
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Graphgpt: Graph instruction tuning for large language models
Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Lixin Su, Suqi Cheng, Dawei Yin, and Chao Huang · 2023
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Yingqiang Ge, Wenyue Hua, Jianchao Ji, Juntao Tan, Shuyuan Xu, and Yongfeng Zhang · 2023
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Jiayan Guo, Lun Du, and Hengyu Liu · 2023
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Explanations as features: Llm-based features for text-attributed graphs
Xiaoxin He, Xavier Bresson, Thomas Laurent, and Bryan Hooi · 2023
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Can llms effectively leverage graph structural information: when and why
Jin Huang, Xingjian Zhang, Qiaozhu Mei, and Jiaqi Ma · 2023
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Benchmarking large language models as ai research agents
Qian Huang, Jian Vora, Percy Liang, and Jure Leskovec · 2023
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Large language models on graphs: A comprehensive survey
Bowen Jin, Gang Liu, Chi Han, Meng Jiang, Heng Ji, and Jiawei Han · 2023
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Patton: Language model pretraining on text-rich networks
Bowen Jin, Wentao Zhang, Yu Zhang, Yu Meng, Xinyang Zhang, Qi Zhu, and Jiawei Han · 2023
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A survey of graph meets large language model: Progress and future directions
Yuhan Li, Zhixun Li, Peisong Wang, Jia Li, Xiangguo Sun, Hong Cheng, and Jeffrey Xu Yu · 2023
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Haishuai Wang, Yang Gao, Xin Zheng, Peng Zhang, Hongyang Chen, and Jiajun Bu · 2023
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Can language models solve graph problems in natural language?
Heng Wang, Shangbin Feng, Tianxing He, Zhaoxuan Tan, Xiaochuang Han, and Yulia Tsvetkov · 2023
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A survey on large language model based autonomous agents
Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, et al · 2023
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Automated 3d pre-training for molecular property prediction
Xu Wang, Huan Zhao, Wei-wei Tu, and Quanming Yao · 2023
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Unleashing the power of graph learning through llm-based autonomous agents
Lanning Wei, Zhiqiang He, Huan Zhao, and Quanming Yao · 2023
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Prompt tuning on graph-augmented low-resource text classification
Zhihao Wen and Yuan Fang · 2023
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Automl-gpt: Automatic machine learning with gpt
Shujian Zhang, Chengyue Gong, Lemeng Wu, Xingchao Liu, and Mingyuan Zhou · 2023
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Large graph models: A perspective
Ziwei Zhang, Haoyang Li, Zeyang Zhang, Yijian Qin, Xin Wang, and Wenwu Zhu · 2023
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Graph-toolformer: To empower llms with graph reasoning ability via prompt augmented by chatgpt
Jiawei Zhang · 2023
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Graphtext: Graph reasoning in text space
Jianan Zhao, Le Zhuo, Yikang Shen, Meng Qu, Kai Liu, Michael Bronstein, Zhaocheng Zhu, and Jian Tang · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
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Automl for deep recommender systems: A survey
Ruiqi Zheng, Liang Qu, Bin Cui, Yuhui Shi, and Hongzhi Yin · 2023
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