Biography ๐Ÿ™‹

EN/CN

I am a Ph.D. student in AI & Statistics at the School of Mathematical Sciences, Shanghai Jiao Tong University, supervised by Prof. Mingyang Ren. Before joining SJTU, I completed my bachelorโ€™s degree in Statistics & Computer Science at the School of Statistics, East China Normal University, where I received the Outstanding Undergraduate Thesis Award. In spring 2026, I worked as a research assistant in the Department of Data Science and Artificial Intelligence at The Hong Kong Polytechnic University, mentored by Prof. Binyan Jiang.

My current research focuses on post-training for multimodal foundation models, particularly on-policy distillation for flow matching models. I aim to build post-training algorithms on a statistical machine learning framework, and validate them through large-scale experiments and evals to understand when and why they remain reliable at foundation-model scale.

News ๐Ÿ“ข

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Sep 2026
Starting my Ph.D. at the School of Mathematical Sciences, Shanghai Jiao Tong University, supervised by Prof. Mingyang Ren.
Jul 2026
HYSET is on arXiv and under review at AAAI 2026: set-level tool retrieval for LLM agents, cast as query-conditioned hyperedge prediction. Code, model, and a live demo are released.
Jun 2026
Graduated from East China Normal University with the Outstanding Undergraduate Thesis Award and the Outstanding Undergraduate Graduate honor.
May 2026
HYVINT, our intensity-driven hypergraph generative model, is on arXiv and under review at AAAI 2026.
Apr 2026
Joined the Department of Data Science and Artificial Intelligence, PolyU, as a research assistant with Prof. Binyan Jiang.

Publications ๐Ÿ“„

* corresponding author
HYSET framework
Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Prediction
Xinyi Hong, Pinjun Dong, Xinyang Yu, Binyan Jiang*
Under review, AAAI Conference on Artificial Intelligence (AAAI), 2026 arXiv:2607.25718
HYVINT framework
HYVINT: Intensity-Driven Hypergraph Generation with Variational Embeddings
Xinyi Hong, Shuntuo Xu, Zhou Yu*
Under review, AAAI Conference on Artificial Intelligence (AAAI), 2026 arXiv:2605.16836
Mixed oil length prediction
Enhancing Mixed Oil Length Prediction through Graph Representation Learning
Xinyi Hong, Hai Shu, Zhaoyang Zhang, Jiahao Wang, Lei Chen, Yanfeng Yang*, Ziqi Chen*
Under review, Journal of Pipeline Science and Engineering

Experience ๐Ÿš€

Research Assistant ยท Department of Data Science and Artificial Intelligence

Education ๐ŸŽ“

Shanghai Jiao Tong University 2026.09 - present
Ph.D. in AI & Statistics ยท School of Mathematical Sciences
Supervisor: Prof. Mingyang Ren
East China Normal University 2022.09 - 2026.06
B.S. in Statistics & Computer Science ยท School of Statistics

Awards & Honors ๐Ÿ…

Outstanding Undergraduate Thesis Award East China Normal University 2026.06
Outstanding Undergraduate Graduate East China Normal University 2026.06
National Second Prize (Team Leader) National Undergraduate Statistical Modeling Competition 2024.08
Outstanding Graduate Hefei No.1 High School 2022.06
Finalist, Young Gifted Program Xi’an Jiaotong University 2019.03

Skills & Languages ๐Ÿ› ๏ธ

Artificial Intelligence Multimodal Foundation Models, Flow Matching / Diffusion Models, Post-Training, LLM Agents, Scaling Laws
Statistics High-Dimensional Inference, Empirical Process Theory, Optimal Transport, Variational Inference, Uncertainty Quantification, ODE/SDE
Engineering Python, PyTorch, Flash Attention, FSDP, Megatron-LM, vLLM, SGLang, Slurm
Languages Mandarin (native), English (professional), Cantonese (conversational), Japanese (beginner)
GitHub activity
GitHub contribution graph for stormwther18

Contact ๐Ÿ’Œ

I welcome discussions and potential collaborations on post-training for generative foundation models. Please feel free to contact me at xinyi.hong@sjtu.edu.cn.