Do Large Language Models Possess a Theory of Mind? A Comparative Evaluation Using the Strange Stories Paradigm
研究通过改编的故事测试法比较了五种大型语言模型与人类在心智理论能力上的表现，以探讨这些模型是否能从文本中推断出他人的信念、意图和情感。
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Selected work
Representative Papers
The Strong Secretary Conjecture is True for Linear Matroids
该研究解决了线性拟阵上的秘书问题，证明了强秘书猜想，采用的方法保证了每个最优基元素被选中的概率至少为1/e。
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MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra
本文提出MiNCE框架，利用RKHS理论构建带限函数及其平滑谱的一致性置信包络，并证明了其在无噪声和有噪声观测模型下的强一致性。
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Quantum Circuit and Tensor Network Implementation of the 2D Acoustic Wave Equation
本文通过量子计算范式及经典张量网络等效方法，特别是使用基于矩阵乘积态的求解器，解决了二维声波方程的大规模模拟问题。
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Unrestricted Boolean Multiplicative Complexity of Four-Term Binary Polynomial Multiplication: Rational Places, Hasse Jets, and the Failure of Nonlinear Feedback
研究解决了四项二元多项式乘法的布尔乘法复杂性问题，通过结构化证明方法确定其复杂性为九，并验证了结果。
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Recent publications
Latest Papers
The Strong Secretary Conjecture is True for Linear Matroids
该研究解决了线性拟阵上的秘书问题，证明了强秘书猜想，采用的方法保证了每个最优基元素被选中的概率至少为1/e。
0 citationsRead paper
MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra
本文提出MiNCE框架，利用RKHS理论构建带限函数及其平滑谱的一致性置信包络，并证明了其在无噪声和有噪声观测模型下的强一致性。
0 citationsRead paper
Quantum Circuit and Tensor Network Implementation of the 2D Acoustic Wave Equation
本文通过量子计算范式及经典张量网络等效方法，特别是使用基于矩阵乘积态的求解器，解决了二维声波方程的大规模模拟问题。
0 citationsRead paper
Unrestricted Boolean Multiplicative Complexity of Four-Term Binary Polynomial Multiplication: Rational Places, Hasse Jets, and the Failure of Nonlinear Feedback
研究解决了四项二元多项式乘法的布尔乘法复杂性问题，通过结构化证明方法确定其复杂性为九，并验证了结果。
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Weighted Equitability and Matroid-Constrained Discrepancy
This study addresses weighted fair division and discrepancy theory under matroid constraints, proposing strongly polynomial-time algorithms grounded in local exchange theorems and constructive proofs. Key contributions include establishing weighted matroid partitionability and extending the Beck-Fiala framework to matroid settings, yielding logarithmic discrepancy bounds. The work achieves EF1 and additive approximation guarantees for fair allocation and scheduling optimization while refuting the weighted carpool conjecture. By systematically resolving fairness and discrepancy control challenges in constrained environments, this research provides novel theoretical foundations and efficient algorithmic tools for related combinatorial optimization problems.
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