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Novice Type Error Diagnosis with Natural Language Models

Published in APLAS, 2022

Recommended citation: Geng, C., Ye, H., Li, Y., Han, T., Pientka, B., & Si, X. (2022, November). Novice Type Error Diagnosis with Natural Language Models. In Asian Symposium on Programming Languages and Systems (pp. 196-214). Cham: Springer Nature Switzerland.

Scalar Invariant Networks with Zero Bias

Published in NeurReps@NeurIPS 2023; PMLR 2024, 2023

Recommended citation: Geng, C., Xu, X., Ye, H., & Si, X. Scalar Invariant Networks with Zero Bias. NeurIPS 2023 Workshop on Symmetry and Geometry in Neural Representations; PMLR, 2024. https://proceedings.mlr.press/v228/geng24a.html

An Optimal Structure-Aware Code Difference Framework with MaxSAT-Solver

Published in SRC@SPLASH, 2023

Recommended citation: Ye, H. (2023). An Optimal Structure-Aware Code Difference Framework with MaxSAT-Solver. SPLASH Companion’23, 43.

SAT-DIFF: A Tree Diffing Framework Using SAT Solving

Published in arXiv preprint, 2024

Recommended citation: Geng, C., Ye, H., Zhang, Y., Pientka, B., & Si, X. SAT-DIFF: A Tree Diffing Framework Using SAT Solving. arXiv preprint arXiv:2404.04731, 2024. https://arxiv.org/pdf/2404.04731

Learning Minimal Neural Specifications

Published in NeuS (Oral), 2025

Recommended citation: Geng, C., Wang, Z., Ye, H., & Si, X. Learning Minimal Neural Specifications. NeuS 2025 (Oral). https://proceedings.mlr.press/v288/geng25a.html

LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks

Published in ICLR, 2026

Recommended citation: Geng, C., Zhao, Z., Wang, Z., Ye, H., Jiang, Y., & Si, X. LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks. In International Conference on Learning Representations (ICLR), 2026. https://openreview.net/pdf?id=nqZe43tRY9

Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generative Modeling

Published in NeurIPS, 2026

Recommended citation: Geng, C., Zhang, L., Zhang, M., Wang, Z., Ye, H., & Si, X. Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generative Modeling. In Advances in Neural Information Processing Systems (NeurIPS), 2026. (accepted) https://arxiv.org/pdf/2602.16954

Novice Type Error Diagnosis with Natural Language Models

Published: December 05, 2022

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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