publications

2026

1. EMNLP 2026

   The Strongest Teacher Is Not Always the Best Teacher: Student-Centric Answer Selection

   Zhengyu Hu^*, Zheyuan Xiao^*, Linxin Song, Fengqing Jiang, and 9 more authors

   In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing, 2026

   Main Conference, forthcoming. * Equal contribution.

   Selects verified teacher answers by student-specific learning cost instead of assuming the strongest teacher always teaches best.

   arXiv Bib HTML PDF

   Cited by 0

   @inproceedings{hu2026studentcentric,
     title = {The Strongest Teacher Is Not Always the Best Teacher: Student-Centric Answer Selection},
     author = {Hu, Zhengyu and Xiao, Zheyuan and Song, Linxin and Jiang, Fengqing and Li, Yuetai and Xiong, Zhihan and Liu, Yue and Lin, Junhao and Su, Yao and Hu, Lijie and Ding, Kaize and Xiao, Teng and Poovendran, Radha},
     booktitle = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing},
     year = {2026},
     note = {Main Conference, forthcoming. * Equal contribution.},
   }

2025

1. Findings 2025

   Explaining Length Bias in LLM-Based Preference Evaluations

   Zhengyu Hu, Linxin Song, Jieyu Zhang, Zheyuan Xiao, and 6 more authors

   In Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

   Explains length bias through desirability and information mass, then introduces a length-aligned evaluation protocol.

   DOI arXiv Bib HTML PDF

   Cited by 75

   @inproceedings{hu2025length,
     title = {Explaining Length Bias in LLM-Based Preference Evaluations},
     author = {Hu, Zhengyu and Song, Linxin and Zhang, Jieyu and Xiao, Zheyuan and Wang, Tianfu and Chen, Zhengyu and Yuan, Nicholas Jing and Lian, Jianxun and Ding, Kaize and Xiong, Hui},
     booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2025},
     pages = {6763--6794},
     year = {2025},
     doi = {10.18653/v1/2025.findings-emnlp.358},
   }

2. arXiv 2025

   Population-Aligned Persona Generation for LLM-based Social Simulation

   Zhengyu Hu, Jianxun Lian, Zheyuan Xiao, Max Xiong, and 6 more authors

   arXiv preprint arXiv:2509.10127, 2025

   Builds representative persona sets by aligning LLM-generated profiles with real population-level psychometric distributions.

   arXiv Bib HTML PDF

   Cited by 30

   @article{hu2025persona,
     title = {Population-Aligned Persona Generation for LLM-based Social Simulation},
     author = {Hu, Zhengyu and Lian, Jianxun and Xiao, Zheyuan and Xiong, Max and Lei, Yuxuan and Wang, Tianfu and Ding, Kaize and Xiao, Ziang and Yuan, Nicholas Jing and Xie, Xing},
     journal = {arXiv preprint arXiv:2509.10127},
     year = {2025},
   }

3. NeurIPS 2025

   Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study

   Zhengyu Hu, Jianxun Lian, Zheyuan Xiao, Seraphina Zhang, and 4 more authors

   In Advances in Neural Information Processing Systems 38, 2025

   Introduces a cognitive framework for testing how language models learn from instructors, concepts, and experience.

   arXiv Bib HTML PDF

   Cited by 9

   @inproceedings{hu2025learning,
     title = {Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study},
     author = {Hu, Zhengyu and Lian, Jianxun and Xiao, Zheyuan and Zhang, Seraphina and Wang, Tianfu and Yuan, Nicholas Jing and Xie, Xing and Xiong, Hui},
     booktitle = {Advances in Neural Information Processing Systems 38},
     year = {2025},
   }