Fairness Matters - A Data-Driven Framework Towards Fair and High Performing Facial Recognition Systems. - Yushi Cao; David Berend; Palina Tolmach; Moshe Levy; Guy Amit; Asaf Shabtai; Yuval Elovici; Yang Liu 003 (CoRR, 2020)

Automatic HMI Structure Exploration Via Curiosity-Based Reinforcement Learning. - Yushi Cao; Yan Zheng 002; Shang-Wei Lin 001; Yang Liu 003; Yon Shin Teo; Yuxuan Toh; Vinay Vishnumurthy Adiga (ASE, 2021)

GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis. - Yushi Cao; Zhiming Li; Tianpei Yang; Hao Zhang 004; Yan Zheng 002; Yi Li 008; Jianye Hao; Yang Liu 003 (NeurIPS, 2022)

A Holistic Automated Software Structure Exploration Framework for Testing. - Yushi Cao; Yon Shin Teo; Yan Zheng 002; Yuxuan Toh; Shang-Wei Lin 001 (SoMeT, 2022)

Fair and accurate age prediction using distribution aware data curation and augmentation. - Yushi Cao; David Berend; Palina Tolmach; Guy Amit; Moshe Levy; Yang Liu 003; Asaf Shabtai; Yuval Elovici (WACV, 2022)

Unveiling Project-Specific Bias in Neural Code Models. - Zhiming Li; Yanzhou Li; Tianlin Li; Mengnan Du; Bozhi Wu; Yushi Cao; Xiaofei Xie; Yi Li 008; Yang Liu 003 (CoRR, 2022)

An Automatic Test Plan Generation Approach for Automotive Software Testing. - Yushi Cao; Yanran Li; Yon Shin Teo; Yan Zheng 002; Zhexin Liang; Shang-Wei Lin 001 (SoMeT, 2023)

Do We Really Need Graph Neural Networks for Traffic Forecasting? - Xu Liu 014; Yuxuan Liang; Chao Huang 001; Hengchang Hu; Yushi Cao; Bryan Hooi; Roger Zimmermann (CoRR, 2023)

Unveiling Project-Specific Bias in Neural Code Models. - Zhiming Li; Yanzhou Li; Tianlin Li; Mengnan Du; Bozhi Wu; Yushi Cao; Junzhe Jiang 002; Yang Liu 003 (LREC/COLING, 2024)

Logic-guided Deep Reinforcement Learning for Stock Trading. - Zhiming Li; Junzhe Jiang 002; Yushi Cao; Aixin Cui; Bozhi Wu; Bo Li 037; Yang Liu 003 (Tiny Papers @ ICLR, 2024)

Improving Neural Logic Machines via Failure Reflection. - Zhiming Li; Yushi Cao; Yan Zheng 002; Xu Liu 014; Bozhi Wu; Tianlin Li; Xiufeng Xu; Junzhe Jiang 002; Yon Shin Teo; Shang-Wei Lin 001; Yang Liu 003 (ICML, 2024)

LLMs for Relational Reasoning: How Far are We? - Zhiming Li; Yushi Cao; Xiufeng Xu; Junzhe Jiang 002; Xu Liu 014; Yon Shin Teo; Shang-Wei Lin 001; Yang Liu 003 (LLM4CODE@ICSE, 2024)

Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency. - Xu Liu 014; Yuxuan Liang; Chao Huang 001; Hengchang Hu; Yushi Cao; Bryan Hooi; Roger Zimmermann (ECML/PKDD (3), 2024)

Logic-Q: Improving Deep Reinforcement Learning-based Quantitative Trading via Program Sketch-based Tuning. - Zhiming Li; Junzhe Jiang 002; Yushi Cao; Aixin Cui; Bozhi Wu; Bo Li 037; Yang Liu 003; Danny Dongning Sun (AAAI, 2025)

Enhancing Vulnerability Detection via Inter-procedural Semantic Completion. - Bozhi Wu; Chengjie Liu; Zhiming Li; Yushi Cao; Jun Sun 001; Shangwei Lin 001 (Proc. ACM Softw. Eng., 2025)

Towards Calibration Enhanced Network by Inverse Adversarial Attack. - Yupeng Cheng; Zi Pong Lim; Sarthak Ketanbhai Modi; Yon Shin Teo; Yushi Cao; Shangwei Lin 001 (CoRR, 2025)

SOSAE: Self-Organizing Sparse AutoEncoder. - Sarthak Ketanbhai Modi; Zi Pong Lim; Yushi Cao; Yupeng Cheng; Yon Shin Teo; Shangwei Lin 001 (CoRR, 2025)

CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks. - Hongchao Jiang; Yiming Chen 010; Yushi Cao; Hung-yi Lee; Robby T. Tan (CoRR, 2025)