Publications

Published

1. Hongkang Li, Meng Wang, Tengfei Ma, Sijia Liu, ZAIXI ZHANG, Pin-Yu Chen. What Improves the Generalization of Graph Transformer? A Theoretical Dive into Self-attention and Positional Encoding. In The Forty-first International Conference on Machine Learning (ICML), 2024.

2. Tong Ye, Lingfei Wu, Tengfei Ma, Xuhong Zhang, Yangkai Du, Peiyu Liu, Wenhai Wang, Shouling Ji. Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization. In NAACL 2024 Findings.

3. Yangkai Du, Tengfei Ma, Lingfei Wu, Xuhong Zhang, Shouling Ji. AdaCCD: Adaptive Semantic Contrasts Discovery based Cross Lingual Adaptation for Code Clone Detection. In Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI) 2024. 

4. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen, Yusu Wang. Cycle Invariant Positional Encoding for Graph Representation Learning. In The Second Learning on Graphs Conference (LOG), 2023. (Oral)

5. EunJeong Hwang, Veronika Thost, Vered Shwartz, Tengfei Ma. Knowledge Graph Compression Enhances Diverse Commonsense Generation. In The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

6. Tong Ye, Lingfei Wu, Tengfei Ma, Xuhong Zhang, Yangkai Du, Peiyu Liu, Wenhai Wang, Shouling Ji. CP-BCS: Binary Code Summarization Guided by Control Flow Graph and Pseudo Code. In The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

7. Yuting Hu, Jiajie Li, Florian Klemme, Gi-Joon Nam, Tengfei Ma, Hussam Amrouch, Jinjun Xiong. SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network. In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023.

8. Nate T. Garland*, Joseph W. Song*, Tengfei Ma*, Yong Jae Kim*, Abraham Vázquez-Guardado, Ayemeh Bagheri Hashkavayi, Sankalp Koduvayur Ganeshan, Nivesh Sharma, Hanjun Ryu, Min-Kyu Lee, Brandon Sumpio, Margaret A. Jakus, Viviane Forsberg, Rajaram Kaveti, Samuel K. Sia, Aristidis Veves, John A. Rogers, Guillermo A. Ameer, Amay J. Bandodkar. A Miniaturized, Battery-free, Wireless Wound Monitor that Predicts Wound Closure Rate Early. In Advanced Healthcare Materials, 2023. (* equal contribution)

9. 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. In KDD 2023 Applied Data Science (ADS) track.

10. Tengfei Ma, Trong Nghia Hoang, Jie Chen. Federated Learning of Models Pre-Trained on Different Features with Consensus Graphs. In The 39th Conference on Uncertainty in Artificial Intelligence (UAI), 2023.

11. Fengjie Wang, Xuye Liu, Oujing Liu, Ali Neshati, Tengfei Ma, Min Zhu, Jian Zhao. Slide4N: Creating Presentation Slides from Computational Notebooks with Human-AI Collaboration. In CHI 2023. 

12. Ruixuan Yan, Yunshi Wen, Debarun Bhattacharjya, Ronny Luss, Tengfei Ma, Achille Fokoue, Anak Agung Julius. Weighted Clock Logic Point Process. In The Eleventh International Conference on Learning Representations (ICLR), 2023.

13. EunJeong Hwang, Veronika Thost, Shib Sankar Dasgupta, Tengfei Ma. An Analysis of Virtual Nodes in Graph Neural Networks for Link Prediction (Extended Abstract). In The First Learning on Graphs Conference (LoG), 2022. (Spotlight)

14. Hongyu Tu, Shantam Shorewala, Tengfei Ma, Veronika Thost. Retrosynthesis Prediction Revisited. In NeurIPS 2022 Workshop AI4Science, 2022.

15. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen. Neural Approximation of Extended Persistent Homology on Graphs. In Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.

16. Ruixuan Yan, Tengfei Ma, Achille Fokoue, Maria Chang, and Agung Julius. Neuro-symbolic Models for Interpretable Time Series Classification using Temporal Logic Description. In the 22nd IEEE International Conference on Data Mining (ICDM), 2022.

17. Zhixian Chen, Tengfei Ma, Zhihua Jin, Yangqiu Song, Yang Wang. BiGCN: A Bi-directional Low-Pass Filtering Graph Neural Network. In Analysis and Applications (special issue of AA 20th Anniversary), 2022. 

18. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen. Cycle Representation Learning for Inductive Relation Prediction. In The 39th International Conference on Machine Learning (ICML), 2022.

19. Weimin Lyu, Songzhu Zheng, Tengfei Ma, Chao Chen. A Study of the Attention Abnormality in Trojaned BERTs. In The 2022 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT), 2022.

20. Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu. GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks. In IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022.

21. Xiang Ling, Lingfei Wu, Wei Deng, Zhengqing Qu, Jiangyu Zhang, Sheng Zhang, Tengfei Ma, Bin Wang, Chunming Wu, and Shouling Ji , "MalGraph: Hierarchical Graph Neural Networks for Robust Windows Malware Detection", In the International Conference on Computer Communications (INFOCOM), 2022.

22. Cao Xiao, Trong Nghia Hoang, Shenda Hong, Tengfei Ma, and Jimeng Sun. CHEER: Rich Model Helps Poor Model via Knowledge Infusion. In Transactions on Knowledge and Data Engineering (TKDE), 2022.

23. Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji and Kathleen McKeown. Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport. In The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021.

24. Yangkai Du, Tengfei Ma, Lingfei Wu, Fangli Xu, Xuhong Zhang, Bo Long and Shouling Ji. Constructing contrastive samples via summarization for text classification with limited annotations. In The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP) Findings, 2021.

25. Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp and Jens Lehmann. Improving Inductive Link Prediction Using Hyper-Relational Facts. In The 20th International Semantic Web Conference (ISWC), 2021. (Best Paper Award - Research Track)

26. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen. Link Prediction with Persistence Homology: An Interactive View. In The Thirty-eighth International Conference on Machine Learning (ICML), 2021.

27. Hanlu Wu, Tengfei Ma, Lingfei Wu, Shouling Ji. Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing. In ACM Transactions on Knowledge Discovery from Data (TKDD), 2021. 

28. Tengfei Ma*, Jie Chen*. Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport. In AAAI 2021. (*equal contribution.)

29. Xiang Ling, Lingfei Wu, Saizhuo Wang, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, Shouling Ji. Hierarchical Graph Matching Networks for Deep Graph Similarity Learning. In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.

30. Xiang Ling, Lingfei Wu, Saizhuo Wang, Gaoning Pan, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu, and Shouling Ji, Deep Graph Matching and Searching for Semantic Code Retrieval, In ACM Transactions on Knowledge Discovery from Data (TKDD), 2021. 

31. Xiao Qin, Cao Xiao, Tengfei Ma, Tabassum Kakar, Susmitha Wunnava, Xiangnan Kong, Elke A. Rundensteiner, Fei Wang . Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding. In Proceedings of the IEEE International Conference on Big Data (BigData), 2020. 

32. Hanlu Wu*, Tengfei Ma*, Lingfei Wu, Tariro Manyumwa, Shouling Ji. Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning. In The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020. (*equal contribution.) [code]

33. Arthur Feeney*, Rishabh Gupta*, Veronika Thost, Rico Angell, Gayathri Chandu, Yash Adhikari and Tengfei Ma. Relation-Dependent Sampling for Multi-Relational Link Prediction. In the Graph Representation Learning and Beyond (GRL+) Workhop at ICML 2020. [Video]

34. Zhao Qin*, Lingfei Wu*, Hui Sun*, Siyu Huo, Tengfei Ma, Eugene Lim, Pin-Yu Chen, Benedetto Marelli, and Markus J. Buehler. Artificial intelligence method to design and fold alpha-helix structural proteins from the primary amino acid sequence. In Extreme Mechanics Letters, 2020.

35. Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen. Curvature Graph Network. In the Eighth International Conference on Learning Representations (ICLR2020).

36. Aldo Pareja*, Giacomo Domeniconi*, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Charles E. Leisersen. EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. In AAAI2020. [AML Transaction Graph Dataset]

37. Tengfei Ma, Patrick Ferber, Siyu Huo, Jie Chen and Michael Katz. Online Planner Selection with Graph Neural Networks and Adaptive Scheduling. In AAAI 2020, Oral. [Planning Graph Datasets]

38. Kaylin Hagopian, Qing Wang, Tengfei Ma, Yupeng Gao and Lingfei Wu. Learning Logical Representations from Natural Languages with Weak Supervision and Back Translation. In the Thirty-third annual conference on Neural Information Processing Systems (NeurIPS 2019) workshop on Knowledge Representation & Reasoning Meets Machine Learning. 

39. Chul Sung, Tejas Dhamecha, Swarnadeep Saha, Tengfei Ma, Vinay Reddy and Rishi Arora. Pre-Training BERT on Domain Resources for Short Answer Grading. In EMNLP-IJCNLP, 2019.

40. Siyu Huo, Tengfei Ma, Jie Chen, Maria Chang, Lingfei Wu, Michael Witbrock. Graph Enhanced Cross-Domain Text-to-SQL Generation. In EMNLP2019 TextGraphs workshop. 

41. Yong Wang, Zhihua Jin, Qianwen Wang, Weiwei Cui, Tengfei Ma, Huamin Qu. DeepDrawing: A Deep Learning Approach to Graph Drawing. In IEEE Transactions on Visualization and Computer Graphics (Proceedings of InfoVis), 2019. [Project Page] [Code] [Video]

42. Tianfan Fu*, Tian Gao*, Cao Xiao, Tengfei Ma, Jimeng Sun. PEARL: Prototype Learning via Rule Learning. In ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), 2019. 

43. Patrick Ferber, Tengfei Ma, Siyu Huo, Jie Chen and Michael Katz. IPC: A Benchmark Data Set for Learning with Graph-Structured Data. In ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data, 2019. (The dataset is also used for our another paper "Online Planner Selection with Graph Neural Networks and Adaptive Scheduling".)

44. Junyuan Shang, Tengfei Ma, Cao Xiao, and Jimeng Sun. Pre-training of Graph Augmented Transformers for Medication Recommendation. In The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. 

45. Shenda Hong, Cao Xiao, Nghia Hoang, Tengfei Ma, Hongyan Li and Jimeng Sun. RDPD: Rich Data Helps Poor Data via Imitation. In The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. 

46. Shenda Hong, Cao Xiao, Tengfei Ma, Hongyan Li and Jimeng Sun. MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals. In The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. 

47. Zhongshu Gu, Hani Jamjoom, Dong Su, Heqing Huang, Jialong Zhang, Tengfei Ma, Dimitrios Pendarakis, Ian Molloy. Reaching Data Confidentiality and Model Accountability on the CalTrain. In the 49th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2019.

48. Junyuan Shang, Cao Xiao, Tengfei Ma, Hongyan Li, Jimeng Sun. GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination. In the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019.

49. Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Timothy Kaler and Hiroki Kanezashi. Scalable Graph Learning for Anti-Money Laundering: A First Look. In NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy (FEAP-AI4Fin), 2018.

50. Tengfei Ma*, Jie Chen*, Cao Xiao. Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders. In Neural Information Processing Systems (NeurIPS), 2018. (*Equal contribution.) [Poster]

51. Tengfei Ma, Cao Xiao, Jiayu Zhou, Fei Wang. Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders. In the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI), 2018.  [Codes]

52. Matthew Ventura, Maria Chang, Peter Foltz, Nirmal Mukhi, Jessica Yarbro, Anne Pier Salverda, John Behrens, Jae-Wook Ahn, Tengfei Ma, Tejas Dhamecha, Smit Marvaniya, Patrick Watson, Cassius D’helon, Ravi Tejwani and Shazia Afzal. Preliminary Evaluations of a Dialogue-based Tutor. In the 19th International Conference on Artificial Intelligence in Education (AIED), 2018.

53. Maria Chang, Matthew Ventura, Jae-wook Ahn, Peter Foltz, Tengfei Ma, Tejas I. Dhamecha, Smit Marvaniya, Patrick Watson, Cassius D’helon, Amy Wetzel, Andy Packard Haas, Kaitlyn Banaszynski, John Behrens, Gailene Nelson, Sharad C. Sundararajan, Ravi Tejwani, Shazia Afzal, Nirmal Mukhi. Dialogue-based tutoring at scale: Design and Challenges. In the 13th International Conference of the Learning Sciences (ICLS), 2018.

54. Jie Chen*, Tengfei Ma*, Cao Xiao. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In the Sixth International Conference on Learning Representations (ICLR), 2018. (*Equal contribution.) [Codes]

55. Cao Xiao,* Tengfei Ma*, Adji B. Dieng, David Blei, Fei Wang. Readmission Prediction via Deep Contextual Embedding of Clinical Concepts. (*Equal contribution). In PLOS ONE, 2018.

56. Tengfei Ma*, Cao Xiao*, Fei Wang. Health-ATM: A Deep Architecture for Multifaceted Patient Health Record Representation and Risk Prediction. In SIAM International Conference on Data Mining (SDM), 2018. (*Equal contribution)

57. Patrick Watson, Tengfei Ma, Ravi Tejwani, Jaewook Ahn, Maria Chang and Sharad Sundararajan. Human-level multiple choice question guessing without domain knowledge: Machine-learning of framing effects. In Web Conference 2018 (WWW), Cognitive Computing Track, 2018.

58. Tengfei Ma, Tetsuya Nasukawa. Inverted Bilingual Topic Models for Lexicon Extraction from Non-parallel Data. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI),  Melbourne, Australia, 2017.

59. Jae-wook Ahn, Patrick Watson, Maria Chang, Sharad Sundararajan, Tengfei Ma, Nirmal Mukhi, Srijith Prabhu. Wizard’s Apprentice: Cognitive Suggestion Support for Wizard-of-Oz Question Answering. In the 18th International Conference on Artificial Intelligence in Education (AIED), Wuhan, China, 2017.

60. Long Duong, Hiroshi Kanayama, Tengfei Ma, Steven Bird, Trevor Cohn. Multilingual Training of Crosslingual Word Embeddings. In Proceedings of the 2017 Conference on European Chapter of the Association for Computational Linguistics (EACL), Valencia, Spain, 2017.

61. Long Duong, Hiroshi Kanayama, Tengfei Ma, Steven Bird, Trevor Cohn. Learning Crosslingual Word Embeddings without Bilingual Corpora. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP), Austin, Texas, USA, pp. 1285–1295, 2016.

62. Tengfei Ma, Issei Sato, Hiroshi Nakagawa. The Hybrid Nested/Hierarchical Dirichlet Process and its Application to Topic Modeling with Word Differentiation. In the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, USA, pp. 2835-2841, 2015.

63. Tengfei Ma and Hiroshi Nakagawa. Automatically Determining a Proper Length for Multi-document Summarization: A Bayesian Nonparametric Approach. In the 2013 Conference on Empirical Methods on Natural Language Processing (EMNLP), Seattle, USA, pp.736-749, 2013.

64. Jaydeep De, Tengfei Ma, Huiqi Li, M. Dash, and Li Cheng. Automated Tracing of Retinal Blood Vessels Using Graphical Models. In Scandinavian Conference on Image Analysis, pp. 277-289, 2013.

65. Xiaojun Wan, Liang Zong, Xiaojiang Huang, Tengfei Ma, Houping Jia, Yuqian Wu, Jianguo Xiao. Named Entity Recognition in Chinese News Comments on the Web. In the 5th International Joint Conference on Natural Language Processing (IJCNLP), pp. 856-864, 2011.

66. Tengfei Ma, Xiaojun Wan. Multi-Document Summarization Using Minimum Distortion. In Proceedings of the 10th IEEE International Conference on Data Mining (ICDM), Sydney, pp. 354-363, 2010.

67. Houping Jia, Xiaojiang Huang, Tengfei Ma, Xiaojun Wan, Jianguo Xiao. PKUTM participation at TAC 2010 RTE and summarization track. In Proceedings of Text Analysis Conference (TAC),2010.

68. Tengfei Ma, Xiaojun Wan. 2010. Opinion Target Extraction in Chinese News Comments. In Proceedings of the 23rd International Conference on Computational Linguistics (COLING2010), Beijing, pp. 782-790.

69. Chenfeng Wang*, Tengfei Ma*, Liqiang Guo, Xiaojun Wan and Jianguo Xiao. PKUTM Experiments in NTCIR8 MOAT Task. Oral in NTCIR-8, Tokyo, pp. 228-233, 2010.  (*Equal contribution.)