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ORCIDYao Ma 0001
Person information
- affiliation: New Jersey Institute of Technology, Newark, NJ, USA
- affiliation: Michigan State University, East Lansing, MI, USA
Other persons with the same name
- Yao Ma — disambiguation page
- Yao Ma 0002
![[0000-0001-6451-8720]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-6451-8720")
— Texas Tech University, Lubbock, TX, USA (and 1 more) - Yao Ma 0004 — National Institute of Standards and Technology, Boulder, CO, USA (and 5 more)
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2020 – today
- 2024
[c51]Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Revisiting Link Prediction: a data perspective. ICLR 2024- [c50]Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Haitao Mao, Qian Chen, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun:
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming. ICML 2024 - [c49]Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang:
Position: Graph Foundation Models Are Already Here. ICML 2024 - [c48]Hongliang Chi, Yao Ma:
Enhancing Contrastive Learning on Graphs with Node Similarity. KDD 2024: 456-465 - [c47]Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang:
LPFormer: An Adaptive Graph Transformer for Link Prediction. KDD 2024: 2686-2698 - [c46]Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma:
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. KDD 2024: 5602-5612 - [c45]Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng:
A Survey on Safe Multi-Modal Learning Systems. KDD 2024: 6655-6665 - [c44]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. SDM 2024: 262-270 - [c43]Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, NhatHai Phan, Yao Ma:
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection. SP 2024: 1236-1254 - [c42]Inwon Kang, Maruf Ahmed Mridul, Abraham Sanders, Yao Ma, Thilanka Munasinghe, Aparna Gupta, Oshani Seneviratne:
Deciphering Crypto Twitter. WebSci 2024: 331-342 - [c41]Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed:
The 5th International Workshop on Machine Learning on Graphs (MLoG). WSDM 2024: 1210-1211 - [c40]Wei Jin, Haohan Wang, Daochen Zha, Qiaoyu Tan, Yao Ma, Sharon Li, Su-In Lee:
DCAI: Data-centric Artificial Intelligence. WWW (Companion Volume) 2024: 1482-1485 - [c39]Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li:
Fast Graph Condensation with Structure-based Neural Tangent Kernel. WWW 2024: 4439-4448 - [i45]Hongliang Chi, Wei Jin, Charu Aggarwal, Yao Ma:
Precedence-Constrained Winter Value for Effective Graph Data Valuation. CoRR abs/2402.01943 (2024) - [i44]Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang:
A Data Generation Perspective to the Mechanism of In-Context Learning. CoRR abs/2402.02212 (2024) - [i43]Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang:
Graph Foundation Models. CoRR abs/2402.02216 (2024) - [i42]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. CoRR abs/2402.02321 (2024) - [i41]Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng:
A Survey on Safe Multi-Modal Learning System. CoRR abs/2402.05355 (2024) - [i40]Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma:
Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks. CoRR abs/2402.15680 (2024) - [i39]Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma:
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. CoRR abs/2403.06017 (2024) - [i38]Inwon Kang, Maruf Ahmed Mridul, Abraham Sanders, Yao Ma, Thilanka Munasinghe, Aparna Gupta, Oshani Seneviratne:
Deciphering Crypto Twitter. CoRR abs/2403.06036 (2024) - [i37]Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Qian Chen, Haitao Mao, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun:
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming. CoRR abs/2406.01908 (2024) - [i36]Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma:
Do Neural Scaling Laws Exist on Graph Self-Supervised Learning? CoRR abs/2408.11243 (2024) - 2023
- [j5]Yiqi Wang, Yao Ma, Wei Jin, Chaozhuo Li, Charu Aggarwal, Jiliang Tang:
Customized Graph Nerual Networks. IEEE Data Eng. Bull. 46(2): 108-125 (2023) - [j4]Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang:
Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles. IEEE Trans. Knowl. Data Eng. 35(12): 12415-12429 (2023) - [c38]Juanhui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion? ACL (1) 2023: 10696-10711 - [c37]Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu:
Learning Representations for Hyper-Relational Knowledge Graphs. ASONAM 2023: 253-257 - [c36]Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang:
Towards Fair Graph Neural Networks via Graph Counterfactual. CIKM 2023: 669-678 - [c35]Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang:
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. EMNLP 2023: 14692-14707 - [c34]Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. NeurIPS 2023 - [c33]Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS 2023 - [c32]Juanhui Li, Wei Zeng, Suqi Cheng, Yao Ma, Jiliang Tang, Shuaiqiang Wang, Dawei Yin:
Graph Enhanced BERT for Query Understanding. SIGIR 2023: 3315-3319 - [c31]Tyler Derr, Yao Ma, Benedek Rozemberczki, Neil Shah, Shirui Pan:
The 3rd International Workshop on Machine Learning on Graphs (MLoG). WSDM 2023: 1271-1272 - [i35]Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? CoRR abs/2306.01323 (2023) - [i34]Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. CoRR abs/2306.10453 (2023) - [i33]Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang:
Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective. CoRR abs/2307.04937 (2023) - [i32]Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, NhatHai Phan, Yao Ma:
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection. CoRR abs/2308.11754 (2023) - [i31]Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Revisiting Link Prediction: A Data Perspective. CoRR abs/2310.00793 (2023) - [i30]Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang:
Adaptive Pairwise Encodings for Link Prediction. CoRR abs/2310.11009 (2023) - [i29]Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li:
Fast Graph Condensation with Structure-based Neural Tangent Kernel. CoRR abs/2310.11046 (2023) - [i28]Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang:
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. CoRR abs/2311.01024 (2023) - 2022
- [j3]Rui Miao, Yintao Yang, Yao Ma, Xin Juan, Haotian Xue, Jiliang Tang, Ying Wang, Xin Wang:
Negative samples selecting strategy for graph contrastive learning. Inf. Sci. 613: 667-681 (2022) - [j2]Wenqi Fan, Yao Ma, Qing Li, Jianping Wang, Guoyong Cai, Jiliang Tang, Dawei Yin:
A Graph Neural Network Framework for Social Recommendations. IEEE Trans. Knowl. Data Eng. 34(5): 2033-2047 (2022) - [c30]Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My T. Thai, Xintao Wu:
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. IEEE Big Data 2022: 1582-1587 - [c29]Yufei He, Yao Ma:
SGKD: A Scalable and Effective Knowledge Distillation Framework for Graph Representation Learning. ICDM (Workshops) 2022: 666-673 - [c28]Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang:
Is Homophily a Necessity for Graph Neural Networks? ICLR 2022 - [c27]Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang:
Automated Self-Supervised Learning for Graphs. ICLR 2022 - [c26]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. KDD 2022: 709-719 - [i27]Juan-Hui Li, Yao Ma, Wei Zeng, Suqi Cheng, Jiliang Tang, Shuaiqiang Wang, Dawei Yin:
Graph Enhanced BERT for Query Understanding. CoRR abs/2204.06522 (2022) - [i26]Juan-Hui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Are Graph Neural Networks Really Helpful for Knowledge Graph Completion? CoRR abs/2205.10652 (2022) - [i25]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. CoRR abs/2206.07743 (2022) - [i24]Hongliang Chi, Yao Ma:
Enhancing Graph Contrastive Learning with Node Similarity. CoRR abs/2208.06743 (2022) - [i23]Harry Shomer, Wei Jin, Juan-Hui Li, Yao Ma, Jiliang Tang:
Learning Representations for Hyper-Relational Knowledge Graphs. CoRR abs/2208.14322 (2022) - [i22]Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My Tra Thai, Xintao Wu:
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. CoRR abs/2211.05766 (2022) - 2021
- [c25]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CIKM 2021: 813-822 - [c24]Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah:
A Unified View on Graph Neural Networks as Graph Signal Denoising. CIKM 2021: 1202-1211 - [c23]Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li:
Attacking Black-box Recommendations via Copying Cross-domain User Profiles. ICDE 2021: 1583-1594 - [c22]Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang:
Elastic Graph Neural Networks. ICML 2021: 6837-6849 - [c21]Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. KDD 2021: 1161-1169 - [c20]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c19]Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang:
Graph Neural Networks with Adaptive Residual. NeurIPS 2021: 9720-9733 - [c18]Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang:
Node Similarity Preserving Graph Convolutional Networks. WSDM 2021: 148-156 - [i21]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CoRR abs/2105.04493 (2021) - [i20]Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang:
Automated Self-Supervised Learning for Graphs. CoRR abs/2106.05470 (2021) - [i19]Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang:
Is Homophily a Necessity for Graph Neural Networks? CoRR abs/2106.06134 (2021) - [i18]Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang:
Elastic Graph Neural Networks. CoRR abs/2107.06996 (2021) - 2020
- [j1]Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain:
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. Int. J. Autom. Comput. 17(2): 151-178 (2020) - [c17]Juan-Hui Li, Yao Ma, Yiqi Wang, Charu C. Aggarwal, Chang-Dong Wang, Jiliang Tang:
Graph Pooling with Representativeness. ICDM 2020: 302-311 - [c16]Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, Jiliang Tang:
Learning from Incomplete Labeled Data via Adversarial Data Generation. ICDM 2020: 1316-1321 - [c15]Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang:
Graph Structure Learning for Robust Graph Neural Networks. KDD 2020: 66-74 - [c14]Yu Rong, Tingyang Xu, Junzhou Huang, Wenbing Huang, Hong Cheng, Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu, Tengfei Ma:
Deep Graph Learning: Foundations, Advances and Applications. KDD 2020: 3555-3556 - [c13]Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li, Jiliang Tang:
Deep Adversarial Canonical Correlation Analysis. SDM 2020: 352-360 - [c12]Yao Ma, Ziyi Guo, Zhaochun Ren, Jiliang Tang, Dawei Yin:
Streaming Graph Neural Networks. SIGIR 2020: 719-728 - [c11]Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu C. Aggarwal, Jiliang Tang:
Epidemic Graph Convolutional Network. WSDM 2020: 160-168 - [c10]Xiaoyang Wang, Yao Ma, Yiqi Wang, Wei Jin, Xin Wang, Jiliang Tang, Caiyan Jia, Jian Yu:
Traffic Flow Prediction via Spatial Temporal Graph Neural Network. WWW 2020: 1082-1092 - [i17]Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li:
Attacking Black-box Recommendations via Copying Cross-domain User Profiles. CoRR abs/2005.08147 (2020) - [i16]Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang:
Graph Structure Learning for Robust Graph Neural Networks. CoRR abs/2005.10203 (2020) - [i15]Yiqi Wang, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Non-IID Graph Neural Networks. CoRR abs/2005.12386 (2020) - [i14]Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah:
A Unified View on Graph Neural Networks as Graph Signal Denoising. CoRR abs/2010.01777 (2020) - [i13]Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang:
Node Similarity Preserving Graph Convolutional Networks. CoRR abs/2011.09643 (2020)
2010 – 2019
- 2019
- [c9]Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li:
Deep Adversarial Social Recommendation. IJCAI 2019: 1351-1357 - [c8]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. KDD 2019: 723-731 - [c7]Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li:
Deep social collaborative filtering. RecSys 2019: 305-313 - [c6]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. SDM 2019: 657-665 - [c5]Wenqi Fan, Yao Ma, Qing Li, Yuan He, Yihong Eric Zhao, Jiliang Tang, Dawei Yin:
Graph Neural Networks for Social Recommendation. WWW 2019: 417-426 - [i12]Wenqi Fan, Yao Ma, Qing Li, Yuan He, Yihong Eric Zhao, Jiliang Tang, Dawei Yin:
Graph Neural Networks for Social Recommendation. CoRR abs/1902.07243 (2019) - [i11]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. CoRR abs/1904.13107 (2019) - [i10]Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li:
Deep Adversarial Social Recommendation. CoRR abs/1905.13160 (2019) - [i9]Yao Ma, Suhang Wang, Lingfei Wu, Jiliang Tang:
Attacking Graph Convolutional Networks via Rewiring. CoRR abs/1906.03750 (2019) - [i8]Zhiwei Wang, Yao Ma, Zitao Liu, Jiliang Tang:
R-Transformer: Recurrent Neural Network Enhanced Transformer. CoRR abs/1907.05572 (2019) - [i7]Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li:
Deep Social Collaborative Filtering. CoRR abs/1907.06853 (2019) - [i6]Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain:
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. CoRR abs/1909.08072 (2019) - 2018
- [c4]Yao Ma, Suhang Wang, Jiliang Tang:
Local and Global Information Preserved Network Embedding. ASONAM 2018: 222-225 - [c3]Tyler Derr, Yao Ma, Jiliang Tang:
Signed Graph Convolutional Networks. ICDM 2018: 929-934 - [c2]Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin:
Multi-Dimensional Network Embedding with Hierarchical Structure. WSDM 2018: 387-395 - [i5]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. CoRR abs/1808.06099 (2018) - [i4]Zhiwei Wang, Yao Ma, Dawei Yin, Jiliang Tang:
Linked Recurrent Neural Networks. CoRR abs/1808.06170 (2018) - [i3]Tyler Derr, Yao Ma, Jiliang Tang:
Signed Graph Convolutional Network. CoRR abs/1808.06354 (2018) - [i2]Yao Ma, Ziyi Guo, Zhaochun Ren, Yihong Eric Zhao, Jiliang Tang, Dawei Yin:
Dynamic Graph Neural Networks. CoRR abs/1810.10627 (2018) - 2017
- [c1]Yao Ma, Suhang Wang, Jiliang Tang:
Network Embedding with Centrality Information. ICDM Workshops 2017: 1144-1145 - [i1]Yao Ma, Suhang Wang, Zhaochun Ren, Dawei Yin, Jiliang Tang:
Preserving Local and Global Information for Network Embedding. CoRR abs/1710.07266 (2017)
Coauthor Index
Juanhui Li
aka: Juan-Hui Li
aka: Juan-Hui Li
[c51] [c50] [c49] [c47] [i44] [i43] [i37] [j5] [j4] [c38] [c35] [c34] [c33] [c32] [i35] [i34] [i31] [i30] [i28] [j3] [j2] [c28] [c27] [c26] [i27] [i26] [i25] [i23] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [i21] [i20] [i19] [i18] [j1] [c17] [c16] [c15] [c13] [c12] [c11] [c10] [i17] [i16] [i15] [i14] [i13] [c9] [c8] [c7] [c6] [c5] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [c4] [c3] [c2] [i5] [i4] [i3] [i2] [c1] [i1]
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