28 citations · 39 across the 8 of their papers we have counts for
10 papers
Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching
Kewen Peng, Yicheng Yang, Hao Zhuo
Fairness-aware learning aims to mitigate discrimination against specific protected social groups (e.g., those categorized by gender, ethnicity, age) while minimizing predictive per…
Software Engineering Principles for Fairer Systems: Experiments with GroupCART
Kewen Peng, Hao Zhuo, Yicheng Yang +1
Discrimination-aware classification aims to make accurate predictions while satisfying fairness constraints. Traditional decision tree learners typically optimize for information g…
Combating Toxic Language: A Review of LLM-Based Strategies for Software Engineering
Hao Zhuo, Yicheng Yang, Kewen Peng
Large Language Models (LLMs) have become integral to Software Engineering (SE), increasingly used in development workflows. However, their widespread adoption raises concerns about…
Context Retrieval via Normalized Contextual Latent Interaction for Conversational Agent
Junfeng Liu, Zhuocheng Mei, Kewen Peng +1
Conversational agents leveraging AI, particularly deep learning, are emerging in both academic research and real-world applications. However, these applications still face challeng…
FairMask: Better Fairness via Model-based Rebalancing of Protected Attributes
Kewen Peng, Joymallya Chakraborty, Tim Menzies
Context: Machine learning software can generate models that inappropriately discriminate against specific protected social groups (e.g., groups based on gender, ethnicity, etc). Mo…
Fairer Software Made Easier (using "Keys")
Tim Menzies, Kewen Peng, Andre Lustosa
Can we simplify explanations for software analytics? Maybe. Recent results show that systems often exhibit a "keys effect"; i.e. a few key features control the rest. Just to say th…
VEER: Enhancing the Interpretability of Model-based Optimizations
Kewen Peng, Christian Kaltenecker, Norbert Siegmund +2
Many software systems can be tuned for multiple objectives (e.g., faster runtime, less required memory, less network traffic or energy consumption, etc.). Optimizers built for diff…
Making Fair ML Software using Trustworthy Explanation
Joymallya Chakraborty, Kewen Peng, Tim Menzies
Machine learning software is being used in many applications (finance, hiring, admissions, criminal justice) having a huge social impact. But sometimes the behavior of this softwar…
Defect Reduction Planning (using TimeLIME)
Kewen Peng, Tim Menzies
Software comes in releases. An implausible change to software is something that has never been changed in prior releases. When planning how to reduce defects, it is better to use p…
How to Improve AI Tools (by Adding in SE Knowledge): Experiments with the TimeLIME Defect Reduction Tool
Kewen Peng, Tim Menzies
AI algorithms are being used with increased frequency in SE research and practice. Such algorithms are usually commissioned and certified using data from outside the SE domain. Can…