Chuqin (Allen) Geng

I am a Computer Science Ph.D. student at McGill University and Mila - Quebec AI Institute. I am currently a visiting scholar at the University of Toronto (U of T), working with Prof. Xujie Si. Prior to that, I earned my M.Sc. in Computer Science at Georgia Tech, and my B.Sc. in Math & Statistics at the University of Toronto.

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Research

I am broadly interested in neuro-symbolic methods and interpretability, with the goal of building AI systems that are more transparent and reliable. My past work has focused on neural network verification and interpretable, reliable learning in the graph domain, and I'm now extending these ideas to large language models.

Selected Papers

Are We Recovering Mechanisms? Objective-Level Recovery Gaps in Mechanistic Interpretability
Chuqin Geng, Li Zhang, Haolin Ye, Mark Zhang, Luke Zhang, Xujie Si
arXiv preprint, 2026
Rethinking Circuit Evaluation: Do Circuits Explain Model Errors? [paper]
Li Zhang*, Chuqin Geng*, Mark Zhang, Chen Yang, Luke Zhang, Haolin Ye, Xujie Si
arXiv preprint, 2026
VisionLogic: Discovering and Grounding Decision-Relevant Visual Concepts [paper]
Chuqin Geng, Yuhe Jiang, Li Zhang, Zhaoyue Wang, Haolin Ye, Mark Zhang, Jingkai Xu, Xujie Si
arXiv preprint, 2026
Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning [paper]
Chuqin Geng, Li Zhang, Haolin Ye, Ziyu Zhao, Yuhe Jiang, Tara Saba, Xinyu Wang, Xujie Si
arXiv preprint, 2026
Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generation with Hard Constraints [paper]
Chuqin Geng, Li Zhang, Mark Zhang, Haolin Ye, Ziyu Zhao, Xujie Si
NeurIPS 2026
DreamProver: Evolving Transferable Lemma Libraries via a Wake-Sleep Theorem-Proving Agent [paper]
Youyuan Zhang*, Jialiang Sun*, Hangrui Bi, Chuqin Geng, Wenjie Ma, Zhaoyu Li, Xujie Si
COLM 2026
LogicXGNN: Grounded Logical Rules for Explaining Graph Neural Networks [paper]
Chuqin Geng, Ziyu Zhao, Zhaoyue Wang, Haolin Ye, Yuhe Jiang, Xujie Si
ICLR 2026 (Top ~2%)
NEUROLOGIC: From Neural Representations to Interpretable Logic Rules [paper]
Chuqin Geng, Anqi Xing, Li Zhang, Ziyu Zhao, Yuhe Jiang, Xujie Si
UCRL Workshop @ ICLR, 2026
Learning Minimal Neural Specifications [paper]
Chuqin Geng, Zhaoyue Wang, Haolin Ye, Xujie Si
NeuS 2025 (Oral)
Towards Robust Saliency Maps [paper]
Van Nham Le*, Chuqin Geng*, Xujie Si, Arie Gurfinkel
ACML 2024
Towards Reliable Neural Specifications [paper]
Chuqin Geng*, Van Nham Le*, Xiaojie Xu, Zhaoyue Wang, Arie Gurfinkel, Xujie Si
ICML 2023 (Oral)
Identifying Different Student Clusters in Functional Programming Assignments: From Quick Learners to Struggling Students [paper]
Chuqin Geng, Wenwen Xu, Yingjie Xu, Brigitte Pientka, Xujie Si
SIGCSE TS 2023
TorchProbe: Fuzzing Dynamic Deep Learning Compilers [paper]
Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si
APLAS 2023
Scalar Invariant Networks with Zero Bias [paper]
Chuqin Geng, Xiaojie Xu, Haolin Ye, Xujie Si
NeurReps Workshop @ NeurIPS, 2023
Novice Type Error Diagnosis with Natural Language Models [paper]
Chuqin Geng, Haolin Ye, Yixuan Li, Tianyu Han, Brigitte Pientka, Xujie Si
APLAS 2022

Academic Service

I contribute to academic service through conference reviewing and student selection:

  • Machine Learning: ICML (2023–2026), ICLR (2024–2027), NeurIPS (2023–2026), AAAI (2024–2027)
  • Computer Vision: CVPR (2024, 2025), ECCV 2026
  • HCI & Education: SIGCSE 2023, CHI 2023
  • Supervision Evaluation Committee Member: Mila Supervision Request Process 2027

Miscellaneous

Outside of research, I spend a lot of time outdoors, hiking and fishing whenever I get the chance. Being out in nature is when I do my best thinking, about how humans, animals, and the rest of the natural world all fit together, and how intelligence came to be in the first place. I also enjoy reading about paleontology, geology, and evolutionary biology in my spare time.