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ORCIDXiang Song 0003
Person information
- affiliation: AWS AI, Santa Clara, CA, USA
Other persons with the same name
- Xiang Song — disambiguation page
- Xiang Song 0001
![[0000-0003-0235-3734]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-0235-3734")
— University of Portsmouth, School of Mathematics and Physics, Portsmouth, UK - Xiang Song 0002 (aka: Xiang (Ben) Song) — Massachusetts Institute of Technology, Cambridge, MA, USA
- Xiang Song 0004 — Nanjing Xiaozhuang University, School of Electronic Engineering, Nanjing, China
- Xiang Song 0005 — Xi'an Jiaotong University, Xi'an, China
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Journal Articles
- 2024
[j2]Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang:
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training. Proc. VLDB Endow. 17(6): 1473-1486 (2024)- 2022
- [j1]Hongkuan Zhou, Da Zheng, Israt Nisa, Vassilis N. Ioannidis, Xiang Song, George Karypis:
TGL: A General Framework for Temporal GNN Training onBillion-Scale Graphs. Proc. VLDB Endow. 15(8): 1572-1580 (2022)
Conference and Workshop Papers
- 2024
- [c17]Kun Wu, Mert Hidayetoglu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-Mei Hwu:
Hector: An Efficient Programming and Compilation Framework for Implementing Relational Graph Neural Networks in GPU Architectures. ASPLOS (3) 2024: 528-544 - [c16]Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos:
NetInfoF Framework: Measuring and Exploiting Network Usable Information. ICLR 2024 - [c15]Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications. KDD 2024: 6356-6367 - [c14]Jing Zhu, Xiang Song, Vassilis N. Ioannidis, Danai Koutra, Christos Faloutsos:
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning. SIGIR 2024: 2662-2666 - [c13]Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra:
Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices. WSDM 2024: 994-1002 - 2023
- [c12]Jiahang Li, Yakun Song, Xiang Song, David Wipf:
On the Initialization of Graph Neural Networks. ICML 2023: 19911-19931 - [c11]Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-Mei Hwu:
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research. KDD 2023: 4284-4295 - [c10]Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi:
Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications. KDD 2023: 5270-5281 - [c9]Jian Zhang, Da Zheng, Xiang Song, Theodore Vasiloudis, Israt Nisa, Jim Lu:
GraphStorm an Easy-to-use and Scalable Graph Neural Network Framework: From Beginners to Heroes. KDD 2023: 5790-5791 - [c8]Zhenkun Cai, Qihui Zhou, Xiao Yan, Da Zheng, Xiang Song, Chenguang Zheng, James Cheng, George Karypis:
DSP: Efficient GNN Training with Multiple GPUs. PPoPP 2023: 392-404 - [c7]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. SC 2023: 39:1-39:12 - [c6]Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun:
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction. WWW 2023: 3784-3793 - 2022
- [c5]Seungwon Min, Kun Wu, Mert Hidayetoglu, Jinjun Xiong, Xiang Song, Wen-Mei Hwu:
Graph Neural Network Training and Data Tiering. KDD 2022: 3555-3565 - [c4]Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, George Karypis:
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs. KDD 2022: 4582-4591 - 2021
- [c3]Da Zheng, Minjie Wang, Quan Gan, Xiang Song, Zheng Zhang, George Karypis:
Scalable Graph Neural Networks with Deep Graph Library. WSDM 2021: 1141-1142 - 2020
- [c2]Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis:
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. IA3@SC 2020: 36-44 - [c1]Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis:
DGL-KE: Training Knowledge Graph Embeddings at Scale. SIGIR 2020: 739-748
Informal and Other Publications
- 2024
- [i24]Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos:
NetInfoF Framework: Measuring and Exploiting Network Usable Information. CoRR abs/2402.07999 (2024) - [i23]Tengfei Ma, Xiang Song, Wen Tao, Mufei Li, Jiani Zhang, Xiaoqin Pan, Jianxin Lin, Bosheng Song, Xiangxiang Zeng:
KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion. CoRR abs/2404.03893 (2024) - [i22]Qi Zhu, Da Zheng, Xiang Song, Shichang Zhang, Bowen Jin, Yizhou Sun, George Karypis:
Parameter-Efficient Tuning Large Language Models for Graph Representation Learning. CoRR abs/2404.18271 (2024) - [i21]Da Zheng, Xiang Song, Qi Zhu, Jiani Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: all-in-one graph machine learning framework for industry applications. CoRR abs/2406.06022 (2024) - [i20]Shichang Zhang, Da Zheng, Jiani Zhang, Qi Zhu, Xiang Song, Soji Adeshina, Christos Faloutsos, George Karypis, Yizhou Sun:
Hierarchical Compression of Text-Rich Graphs via Large Language Models. CoRR abs/2406.11884 (2024) - 2023
- [i19]Kun Wu, Mert Hidayetoglu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-Mei W. Hwu:
PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks. CoRR abs/2301.06284 (2023) - [i18]Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang:
ReFresh: Reducing Memory Access from Exploiting Stable Historical Embeddings for Graph Neural Network Training. CoRR abs/2301.07482 (2023) - [i17]Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun:
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction. CoRR abs/2302.12465 (2023) - [i16]Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei W. Hwu:
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research. CoRR abs/2302.13522 (2023) - [i15]Jing Zhu, Yuhang Zhou, Vassilis N. Ioannidis, Shengyi Qian, Wei Ai, Xiang Song, Danai Koutra:
SpotTarget: Rethinking the Effect of Target Edges for Link Prediction in Graph Neural Networks. CoRR abs/2306.00899 (2023) - [i14]Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, Trishul Chilimbi:
Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications. CoRR abs/2306.02592 (2023) - [i13]Hongkuan Zhou, Da Zheng, Xiang Song, George Karypis, Viktor K. Prasanna:
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training. CoRR abs/2307.07649 (2023) - [i12]Jing Zhu, Xiang Song, Vassilis N. Ioannidis, Danai Koutra, Christos Faloutsos:
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning. CoRR abs/2309.13885 (2023) - [i11]Jiahang Li, Yakun Song, Xiang Song, David Paul Wipf:
On the Initialization of Graph Neural Networks. CoRR abs/2312.02622 (2023) - 2022
- [i10]Hongkuan Zhou, Da Zheng, Israt Nisa, Vasileios Ioannidis, Xiang Song, George Karypis:
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs. CoRR abs/2203.14883 (2022) - [i9]Bo He, Xiang Song, Vincent Gao, Christos Faloutsos:
ColdGuess: A General and Effective Relational Graph Convolutional Network to Tackle Cold Start Cases. CoRR abs/2205.12318 (2022) - [i8]Vassilis N. Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, George Karypis:
Efficient and effective training of language and graph neural network models. CoRR abs/2206.10781 (2022) - 2021
- [i7]Seungwon Min, Kun Wu, Mert Hidayetoglu, Jinjun Xiong, Xiang Song, Wen-mei W. Hwu:
Graph Neural Network Training with Data Tiering. CoRR abs/2111.05894 (2021) - [i6]Xiang Song, Runjie Ma, Jiahang Li, Muhan Zhang, David Paul Wipf:
Network In Graph Neural Network. CoRR abs/2111.11638 (2021) - [i5]Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, Qidong Su, Minjie Wang, Chao Ma, George Karypis:
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs. CoRR abs/2112.15345 (2021) - 2020
- [i4]Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis:
DGL-KE: Training Knowledge Graph Embeddings at Scale. CoRR abs/2004.08532 (2020) - [i3]Xiangxiang Zeng, Xiang Song, Tengfei Ma, Xiaoqin Pan, Yadi Zhou, Yuan Hou, Zheng Zhang, George Karypis, Feixiong Cheng:
Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning. CoRR abs/2005.10831 (2020) - [i2]Colby Wise, Vassilis N. Ioannidis, Miguel Romero Calvo, Xiang Song, George Price, Ninad Kulkarni, Ryan Brand, Parminder Bhatia, George Karypis:
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature. CoRR abs/2007.12731 (2020) - [i1]Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis:
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR abs/2010.05337 (2020)
Coauthor Index
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