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Pingchuan Ma

Hong Kong University of Science and Technology

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Preprint Oct 2026

Decompiling Quantum Assembly into Structured Programs

This work presents Quelle, a decompiler that recovers structured programs from routed and optimized quantum assembly (OpenQASM) and checks every output for equivalence with its input, and fully decompiles 94% of them.

Pingchuan Ma, Zhan-Tong Xue, Zong-Jie Li et al. · 0 citations
Open access Oct 2026

Function Calling as a Flexible LLM Defense Add-On: Capability and Application Exploration

Large language models (LLMs) exhibit impressive capabilities but are susceptible to adversarial attacks that induce harmful outputs. Although various defenses have been proposed, their practicality is restricted by substantial runtime overhead or degraded model helpfulness. Moreover, LLM applications typically have div...

Zhenlan Ji, Dao-Yuan Wu, Wen-Xuan Wang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Demistifying Data and Simulator Assumptions in Supervised Causal Discovery

This paper organizes methods by prediction target, prediction granularity, encoder, structural decoder, and training regime to relate what each method predicts to how it uses data and simulator-based supervision, and distinguishes two questions: whether the target is identifiable under the assumed model class and wheth...

Pingchuan Ma, Rui Ding, Bojun Huang et al. · 0 citations
Book Open access Aug 2026

One Rounding Fits All: Memory-Efficient Approximation Algorithms for Partition-Constrained Influence Maximization

RBwA, a memory-efficient and sample-efficient progressive sampling algorithm for IM-PC and a memory-efficient rounding scheme called BwARound for coverage maximization subroutines, which only requires storing one fractional vector and takes maximal feasible steps rather than tiny ε-increments, are proposed.

Qixin Zhang, Qirun Zeng, Hui Lu et al. · 0 citations

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