王曦立 (Xili Wang)

王曦立照片

Ph.D.,
School of Mathematical Sciences,
Peking University

Google Scholar

xiliwang17 [AT] fudan.edu.cn

About Me

I received my Ph.D. in Computational Mathematics from the School of Mathematical Sciences, Peking University. Before that, I received my bachelor degree from the School of Mathematical Sciences, Fudan University, majoring in Information and Computational Science and ranking 1/52.

I am currently an LLM Engineer at Meituan LongCat Team.

Education

Peking University, Ph.D.
Sep 2021 - Jun 2026

School of Mathematical Sciences, Computational Mathematics

Fudan University, B.S.
Sep 2017 - Jun 2021

School of Mathematical Sciences, Information and Computational Science, rank 1/52

Louisiana State University, Visiting Scholar
Aug 2024 - Feb 2025

Department of Mathematics, under the supervision of Professor Xiaoliang Wan

Collaborators

Work Experience

Meituan LongCat Team, LLM Engineer, Jun 2026 - Present

Meituan LongCat Team, LLM Intern, Mar 2025 - Sep 2025
Key contributor to agentic tool-use research and development, focusing on tool-use data synthesis, supervised fine-tuning, and reinforcement learning for multi-turn LLM agents.

  • Built two automated multi-turn tool-use data synthesis pipelines based on Multi-LLMs and MCP: a simulation pipeline with task-specific virtual databases and a real-execution pipeline that invokes MCP tools through user-agent-tool interactions.
  • Used the synthesized multi-turn tool-use data for SFT of LongCat-Flash-Chat, a 560B-parameter MoE model, improving its agentic tool-use capability. LongCat-Flash-Chat achieved TAU2 Retail 71, TAU2 Airline 58, and TAU2 Telecom 68 on TAU2-Bench (SOTA as of Jun 2025).
  • Worked on a multi-turn user-interacting reinforcement learning framework for agentic tool use. The work introduces LLM-simulated users into RL rollout so that agents learn to clarify dynamic user requirements, maintain task state, and coordinate tool calls over long interactions.

Research

My research interests include

  • Large language model pre-training
  • Deep adaptive sampling for scientific computing
  • Numerical methods for PDE-constrained optimization problems

Publications and Preprints

Corresponding author.

Patents

  • 杨超, 王曦立, 尹鹏飞, 张博. 形状优化方法及计算机存储介质和终端设备, 中国专利, CN116680763B[P], 2024-05-17.

Invited Talks

  • "AONN-2: An adjoint-oriented neural network method for PDE-constrained shape optimization", SIAM Conference on Mathematics of Data Science (MDS24), Atlanta, Georgia, USA, Oct 2024.
  • "DL for PDEs: towards parametric, high-dimensional and PDE-constrained optimization", Louisiana State University, Baton Rouge, Louisiana, USA, Oct 2024.

Honors and Awards

  • 北京大学数学科学学院“优秀毕业生”,2026 年
  • 2023-2024 学年北京大学优秀科研奖
  • 2023-2024 学年北京大学兴业银行奖学金
  • 2022-2023 学年北京大学“硕博杯”羽毛球比赛第八名
  • 复旦大学“拔尖计划”荣誉学生,2021 年
  • 2020-2021 学年复旦大学本科优秀学生奖学金(毕业生奖学金)
  • 2019-2020 学年复旦大学本科优秀学生奖学金一等奖(董氏奖学金)
  • 2019-2020 学年复旦大学本科生专业奖学金
  • 2018-2019 学年复旦大学本科优秀学生奖学金二等奖
  • 2018-2019 学年复旦大学本科生专业奖学金