Novice Type Error Diagnosis with Natural Language Models. - Chuqin Geng; Haolin Ye; Yixuan Li; Tianyu Han; Brigitte Pientka; Xujie Si (APLAS, 2022)

Toward Reliable Neural Specifications. - Chuqin Geng; Nham Le; Xiaojie Xu; Zhaoyue Wang; Arie Gurfinkel; Xujie Si (CoRR, 2022)

TorchProbe: Fuzzing Dynamic Deep Learning Compilers. - Qidong Su; Chuqin Geng; Gennady Pekhimenko; Xujie Si (APLAS, 2023)

Towards Reliable Neural Specifications. - Chuqin Geng; Nham Le; Xiaojie Xu; Zhaoyue Wang; Arie Gurfinkel; Xujie Si (ICML, 2023)

Scalar Invariant Networks with Zero Bias. - Chuqin Geng; Xiaojie Xu; Haolin Ye; Xujie Si (NeurReps, 2023)

Identifying Different Student Clusters in Functional Programming Assignments: From Quick Learners to Struggling Students. - Chuqin Geng; Wenwen Xu; Yingjie Xu; Brigitte Pientka; Xujie Si (SIGCSE (1), 2023)

Can ChatGPT Pass An Introductory Level Functional Language Programming Course? - Chuqin Geng; Yihan Zhang; Brigitte Pientka; Xujie Si (CoRR, 2023)

Towards Robust Saliency Maps. - Nham Le; Arie Gurfinkel; Xujie Si; Chuqin Geng (ACML, 2024)

Learning Minimal NAP Specifications for Neural Network Verification. - Chuqin Geng; Zhaoyue Wang; Haolin Ye; Saifei Liao; Xujie Si (CoRR, 2024)

SAT-DIFF: A Tree Diffing Framework Using SAT Solving. - Chuqin Geng; Haolin Ye; Yihan Zhang; Brigitte Pientka; Xujie Si (CoRR, 2024)

Learning Minimal Neural Specifications. - Chuqin Geng; Zhaoyue Wang; Haolin Ye; Xujie Si (NeuS, 2025)

Decoding Interpretable Logic Rules from Neural Networks. - Chuqin Geng; Xiaojie Xu; Zhaoyue Wang; Ziyu Zhao 006; Xujie Si (CoRR, 2025)

Learning Interpretable Logic Rules from Deep Vision Models. - Chuqin Geng; Yuhe Jiang; Ziyu Zhao 006; Haolin Ye; Zhaoyue Wang; Xujie Si (CoRR, 2025)

Extracting Interpretable Logic Rules from Graph Neural Networks. - Chuqin Geng; Zhaoyue Wang; Ziyu Zhao 006; Haolin Ye; Xujie Si (CoRR, 2025)