Pingchuan Ma
Pingchuan Ma
Hong Kong University of Science and Technology; UC Berkeley
Verified email at - Homepage
Cited by
Cited by
Metamorphic Testing and Certified Mitigation of Fairness Violations in NLP Models
P Ma, S Wang, J Liu
IJCAI, 458-465, 2020
Metainsight: Automatic discovery of structured knowledge for exploratory data analysis
P Ma, R Ding, S Han, D Zhang
Proceedings of the 2021 international conference on management of data, 1262 …, 2021
Mt-teql: evaluating and augmenting neural nlidb on real-world linguistic and schema variations
P Ma, S Wang
Proceedings of the VLDB Endowment 15 (3), 569-582, 2021
InsightPilot: An LLM-Empowered Automated Data Exploration System
P Ma, R Ding, S Wang, S Han, D Zhang
Proceedings of the 2023 Conference on Empirical Methods in Natural Language …, 2023
On the feasibility of specialized ability stealing for large language code models
Z Li, C Wang, P Ma, C Liu, S Wang, D Wu, C Gao
arXiv e-prints, arXiv: 2303.03012, 2023
Unleashing the power of compiler intermediate representation to enhance neural program embeddings
Z Li, P Ma, H Wang, S Wang, Q Tang, S Nie, S Wu
Proceedings of the 44th International Conference on Software Engineering …, 2022
Security of medical cyber-physical systems: an empirical study on imaging devices
Z Wang, P Ma, X Zou, J Zhang, T Yang
IEEE INFOCOM 2020-IEEE Conference on Computer Communications Workshops …, 2020
Split and merge: Aligning position biases in large language model based evaluators
Z Li, C Wang, P Ma, D Wu, S Wang, C Gao, Y Liu
arXiv preprint arXiv:2310.01432, 2023
Xinsight: explainable data analysis through the lens of causality
P Ma, R Ding, S Wang, S Han, D Zhang
Proceedings of the ACM on Management of Data 1 (2), 1-27, 2023
Oops, Did I Just Say That? Testing and Repairing Unethical Suggestions of Large Language Models with Suggest-Critique-Reflect Process
P Ma, Z Li, A Sun, S Wang
Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach
Z Ji, P Ma, Z Li, S Wang
arXiv preprint arXiv:2310.06680, 2023
Ml4s: Learning causal skeleton from vicinal graphs
P Ma, R Ding, H Dai, Y Jiang, S Wang, S Han, D Zhang
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Explain any concept: Segment anything meets concept-based explanation
A Sun, P Ma, Y Yuan, S Wang
Advances in Neural Information Processing Systems 36, 2024
Enhancing dnn-based binary code function search with low-cost equivalence checking
H Wang, P Ma, Y Yuan, Z Liu, S Wang, Q Tang, S Nie, S Wu
IEEE Transactions on Software Engineering 49 (1), 226-250, 2022
Differentially private reinforcement learning
P Ma, Z Wang, L Zhang, R Wang, X Zou, T Yang
International Conference on Information and Communications Security, 668-683, 2019
Perfce: Performance debugging on databases with chaos engineering-enhanced causality analysis
Z Ji, P Ma, S Wang
2023 38th IEEE/ACM International Conference on Automated Software …, 2023
Noleaks: Differentially private causal discovery under functional causal model
P Ma, Z Ji, Q Pang, S Wang
IEEE Transactions on Information Forensics and Security 17, 2324-2338, 2022
Medical devices are at risk: Information security on diagnostic imaging system
Z Wang, P Ma, Y Chi, J Zhang
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018
On extracting specialized code abilities from large language models: A feasibility study
Z Li, C Wang, P Ma, C Liu, S Wang, D Wu, C Gao, Y Liu
arXiv preprint arXiv:2303.03012, 2023
Unlearnable Examples: Protecting Open-Source Software from Unauthorized Neural Code Learning.
Z Ji, P Ma, S Wang
SEKE, 525-530, 2022
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