I am a fourth-year PhD candidate in the College of Computer Science and Artificial Intelligence at Fudan University, advised by Prof. Xuanjing Huang and Prof. Xipeng Qiu. I am also affiliated with the Institute of Modern Languages and Linguistics.

My research interests lie in understanding the computational principles that underlie language and its interaction with other components of intelligence, particularly those thought to be uniquely human. I apply these insights to evaluate, interpret, and advance AI systems, which in turn provide computational tools for probing the nature of language and intelligence. Currently, my work focuses on the capacity for conceptual representation in AI systems.

Previously, I received my B.A. in Chinese Language and Literature from Fudan University in 2022, where I began my research at the intersection of computational linguistics and AI.

Selected Publications

• Ningyu Xu, Qi Zhang, Chao Du, Qiang Luo, Xipeng Qiu, Xuanjing Huang, and Menghan Zhang. 2025. Revealing emergent human-like conceptual representations from language prediction. Proceedings of the National Academy of Sciences. [paper] [code and data]

• Ningyu Xu, Qi Zhang, Jingting Ye, Menghan Zhang, and Xuanjing Huang. 2023. Are Structural Concepts Universal in Transformer Language Models? Towards Interpretable Cross-Lingual Generalization. In Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics. [paper] [pdf] [code]

• Ningyu Xu, Tao Gui, Ruotian Ma, Qi Zhang, Jingting Ye, Menghan Zhang, and Xuanjing Huang. 2022. Cross-Linguistic Syntactic Difference in Multilingual BERT: How Good is It and How Does It Affect Transfer?. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics. [paper] [pdf] [code]