13 citations · 52 across the 19 of their papers we have counts for
7 papers · 1 filter
Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning (Extended Version)
Pingchuan Ma, Zhenlan Ji, Peisen Yao +2
Causal discovery is a powerful technique for identifying causal relationships among variables in data. It has been widely used in various applications in software engineering. Caus…
Towards Practical Federated Causal Structure Learning
Zhaoyu Wang, Pingchuan Ma, Shuai Wang
Understanding causal relations is vital in scientific discovery. The process of causal structure learning involves identifying causal graphs from observational data to understand s…
Explain Any Concept: Segment Anything Meets Concept-Based Explanation
Ao Sun, Pingchuan Ma, Yuanyuan Yuan +1
EXplainable AI (XAI) is an essential topic to improve human understanding of deep neural networks (DNNs) given their black-box internals. For computer vision tasks, mainstream pixe…
"Oops, Did I Just Say That?" Testing and Repairing Unethical Suggestions of Large Language Models with Suggest-Critique-Reflect Process
Pingchuan Ma, Zongjie Li, Ao Sun +1
As the popularity of large language models (LLMs) soars across various applications, ensuring their alignment with human values has become a paramount concern. In particular, given…
Causality-Aided Trade-off Analysis for Machine Learning Fairness
Zhenlan Ji, Pingchuan Ma, Shuai Wang +1
There has been an increasing interest in enhancing the fairness of machine learning (ML). Despite the growing number of fairness-improving methods, we lack a systematic understandi…
Demonstration of InsightPilot: An LLM-Empowered Automated Data Exploration System
Pingchuan Ma, Rui Ding, Shuai Wang +2
Exploring data is crucial in data analysis, as it helps users understand and interpret the data more effectively. However, performing effective data exploration requires in-depth k…
On Extracting Specialized Code Abilities from Large Language Models: A Feasibility Study
Zongjie Li, Chaozheng Wang, Pingchuan Ma +5
Recent advances in large language models (LLMs) significantly boost their usage in software engineering. However, training a well-performing LLM demands a substantial workforce for…