Author

Yong-Li Ren

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Preprint Jul 2026

Energy Accuracy Is Not Enough: A Structure-Aware Benchmark and Evaluation Protocol for Quantum Architecture Search

HamQASBench is introduced, a structure-aware benchmark comprising eleven molecular Hamiltonians of up to fourteen qubits, selected using Hamiltonian and target-state properties and supplied with exact references, that combines energy accuracy and success rates with reference-relative circuit cost, local entropy profile...

Jia-Yang Niu, Akib Karim, Yan Wang et al. · 0 citations

Preprint Sep 2026

FunnelAudit: Responsibility Auditing in Multi-Route Recommender Systems

Findings demonstrate the importance of explicit serving semantics and checkable witnesses for recommender accountability, and introduce FunnelAudit, an executable framework for incident-level responsibility auditing.

Jie Li, David Luo, Jia-Yang Niu et al. · 0 citations

Book Open access Jul 2026

Mitigating Bias in Large Language Model Based Question Answering through Causal Front Door Prompting

A Causal Front Door Prompting framework (CFDP) is proposed that reduces demographic influence by intervening on the chain of thought reasoning, which is treated as an observable mediator and consistently improves fairness metrics without sacrificing QA accuracy.

Ya-Qi Yang, Zi-Qi Xu, Jie Li et al. · Annual International ACM SIG... · 1 citation

#quantum computing Preprint Jul 2026

HamQASBench: A Hamiltonian-Informed Diagnostic Benchmark for Evaluating Quantum Architecture Search

Quantum Architecture Search (QAS) automates the design of parameterized quantum circuits for variational quantum algorithms, yet existing benchmarks organize instances by molecular identity or qubit count -- criteria agnostic to Hamiltonian structure -- and rely solely on energy accuracy, which cannot detect structural...

Jiayang Niu, Akib Karim, Yan Wang et al. · 1 citation

#machine learning Preprint Jul 2026

DreamQAS: Learning a Decision-Useful World Model for VQE-Efficient Quantum Architecture Search

These results establish a world-model design for QAS whose value lies in decision-useful feedback rather than exact energy prediction, and establish a world-model design for QAS whose value lies in decision-useful feedback rather than exact energy prediction.

Jiayang Niu, Yan Wang, Jie Li et al. · 0 citations