Yuante Li (李元特)

Yuante Li (李元特)

Master student in NLP at CMU.

I am currently pursuing my Master’s degree in Intelligent Information Systems (NLP Research Master) at the Language Technologies Institute, School of Computer Science, Carnegie Mellon University, supervised by Prof. Lei Li and Prof. Mona Diab. I am currently a Quantitative Research Intern at Point 72. I also serve as the Co-CTO of LLMQuant. I am currently seeking full-time opportunities in Research Scientist / MLE / Quantitative Researcher. Feel free to reach out to me regarding potential opportunities or collaborations.

Prior to this, I completed my undergraduate studies in Computer Science and Technology at Tongji University, where I worked closely with Academician Changjun Jiang, Prof. Dawei Cheng and Prof. Qinyuan Liu at the Fintech Lab. In addition, I worked with Dean Ke Tang during a research internship at Tsinghua University. I also spent over a year as a research intern in the Machine Learning Group at Microsoft Research, advised by Dr. Jiang Bian.

My research interests focus on:

  • AI Scientist, Recursive Self-Improvement
  • Agentic System
  • Large Language Models
  • Data Mining
  • AI for Finance

📧 Contact

email: yuantel[at]cs[dot]cmu[dot]edu

🔥 News

2026.07Our paper FinMamba received the Oral Paper Award at the SIGKDD 2026 Workshop on Machine Learning in Finance.
2026.06Represented the CMU team and won 1st place among OpenAI-sponsored teams at the Grounded Reasoning Cup organized by Databricks, receiving a $10,000 prize.
2026.06Our paper MiniAppBench was accepted to ICML 2026 as a Spotlight.
2026.05Started as a Quantitative Research Intern at Point72.
2025.10Our paper FinTSB received the Best Paper Award at the ICAIF 2025 Workshop.
2025.09Our paper R&D-Agent-Quant was accepted to NeurIPS 2025.
2025.08Started my M.S. in Intelligent Information Systems at the Language Technologies Institute, CMU.
2025.08Received the Stars of Tomorrow certificate from Microsoft Research Asia, the highest honor for interns (Top 1%).
2025.06Graduated from Tongji University with Top Honors for the Graduation Thesis (Top 0.2%).

💼 Experiences

May, 2026 - present
Quantitative Research Intern @ Point 72
Aug, 2025 - present
Research Assistant @ LI Lab, Carnegie Mellon University
Supervisor: Prof. Lei Li, Prof. Fei Fang
Jun, 2025 - Sept, 2025
Research Assistant @ ULab, University of Illinois Urbana-Champaign
Supervisor: Prof. Jiaxuan You
Aug, 2024 - present
Co-Chief Technology Officer @ LLMQuant
Research, Develop, and Manage in AI + Quant/Finance projects.
Jun, 2024 - Aug, 2025
Research Intern @ Microsoft Research
Supervisor: Dr. Jiang Bian
Jun, 2024 - Dec, 2024
Research Assistant @ Tsinghua University
Supervisor: Dean Ke Tang
Mar, 2024 - Jun, 2024
Quantitative Research Intern @ Taiping Asset Management Co. Ltd.
Jan, 2024 - Feb, 2024
Information Technology Department Intern @ Bank of China
Aug, 2023 - Sep, 2023
Quantitative Research Intern @ CITIC Securities
July, 2023 - June, 2025
Research Assistant @ Fintech Lab, Tongji University
Supervisor: Prof. Changjun Jiang, Prof. Dawei Cheng, Prof. Qinyuan Liu
May, 2022 - Oct, 2023
Research Assistant @ CIMS Research Center, Tongji University
Supervisor: Prof. Fei Qiao

📝 Publications

Notes:（*）indicates the equal contributions. Click a topic to filter.

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NeurIPS 2025
R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization

Yuante Li, Xu Yang, Xiao Yang, Minrui Xu, Xisen Wang, Weiqing Liu, and Jiang Bian

Agentic SystemLLMAI for Finance

📄 Paper 💻 Code Stars & Stars

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Preprint
R&D-Agent: Automating Data-Driven AI Solution Building Through LLM-Powered Automated Research, Development, and Evolution

Xu Yang, Xiao Yang, Shikai Fang, Bowen Xian, Yuante Li (1st intern author), Jian Wang, Minrui Xu, Haoran Pan, Xinpeng Hong, Weiqing Liu, Yelong Shen, Weizhu Chen, and Jiang Bian

Agentic SystemLLM

📄 Paper 💻 Code Stars

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ICML 2026🏅 Spotlight
MiniAppBench: Evaluating the Shift from Text to Interactive HTML Responses in LLM-Powered Assistants

Zuhao Zhang*, Chengyue Yu*, Yuante Li*, Chenyi Zhuang, Linjian Mo, and Shuai Li

LLMBenchmark & Survey

📄 Paper 💻 Code Stars

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ICML 2026
From Observations to States: Latent Time Series Forecasting

Jie Yang, Yifan Hu, Yuante Li, Kexin Zhang, Kaize Ding, and Philip S Yu

Time Series

📄 Paper 💻 Code Stars

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COLM 2026 Workshop
Diverse Evidence, Better Forecasts: Multi-Agent Deliberation Under Information Asymmetry

Yuante Li †, Yicheng Tao, Kate Zhang, Taozhi Wang, Gefei Gu, and Yaxin Zhou

Agentic SystemLLM

📄 Paper

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FCS 2026ICAIF 2025 Workshop🏅 Best Paper
FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting

Yifan Hu*, Yuante Li*, Peiyuan Liu*, Yuxia Zhu, Naiqi Li, Tao Dai, Shu-tao Xia, Dawei Cheng, and Changjun Jiang

Time SeriesAI for FinanceBenchmark & Survey

📄 Paper 💻 Code Stars Awesome-Papers Stars

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Preprint
Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches

Yicheng Tao*,Yuante Li*, Yao Qin, and Yepang Liu

LLMBenchmark & Survey

📄 Paper

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Preprint
The Landscape of Agentic Time Series Systems: Architectures, Reliability, and Frontiers

Yifan Hu, Jie Yang, Xilin Dai, Wanyu Cai, Kuiye Ding, Yuante Li, Qinghua Liu, Enze Ma, Zhiyuan Qu, Yixin Wang, Binyan Xu, Kexin Zhang, Peiyuan Liu, Zhijian Xu, Guibin Zhang, Yujin Tang, Yanwei Yue, Kening Zheng, Chengze Li, Hannong Zhang, Haoyan Xu, Naiqi Li, Tao Dai, Dawei Cheng, John Paparrizos, Kaize Ding, Tian Zhou, Qiang Xu, Shu-tao Xia, Shirui Pan, and Philip S. Yu

Agentic SystemTime SeriesBenchmark & Survey

📄 Paper 💻 Code Stars

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NeurIPS 2025 GenAI Workshop
QuantMind: A Context-Engineering Based Knowledge Framework for Quantitative Finance

Haoxue Wang*, Keli Wen*, Yuante Li*, Qiancheng Qu*, Xiangxu Mu*, Xinjie Shen, Jiaqi Gao, Chenyang Chang, Chuhan Xie, San Yu Cheung, Zhuoyuan Hu, Xinyu Wang, Sirui Bi, and Bi’an Du

LLMAI for Finance

📄 Paper 💻 Code Stars

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CIKM 2024
LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU

Peng Zhu*, Yuante Li*, Yifan Hu, Qinyuan Liu, Dawei Cheng, and Yuqi Liang

AI for FinanceData Mining

📄 Paper 💻 Code Stars

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ICFOD 2024🏅 Excellent Paper
Futures Market Modeling and Forecasting: SOTA Deep Time Series Neural Networks

Yuante Li, Yuhan Cheng, and Ke Tang

Time SeriesAI for Finance

📄 Paper

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TKDE 2025
Financial Time Series Prediction with Multi-granularity Graph Augmented Learning

Peng Zhu, Yuante Li (1st student author), Qinyuan Liu, Dawei Cheng, and Changjun Jiang

AI for FinanceData MiningTime Series

📄 Paper 💻 Code Stars

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Neurocomputing 2025
MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU

Peng Zhu, Yuante Li (1st student author), Yifan Hu, Sheng Xiang, Qinyuan Liu, Dawei Cheng, and Yuqi Liang

AI for FinanceData Mining

📄 Paper 💻 Code Stars

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CIKM 2026SIGKDD 2026 Workshop🏅 Oral
FinMamba: Market-Aware Graph Enhanced Multi-Level Mamba for Stock Movement Prediction

Yifan Hu*, Peiyuan Liu*, Yuante Li, Dawei Cheng, Naiqi Li, Tao Dai, Jigang Bao, and Shu-Tao Xia

Time SeriesAI for Finance

📄 Paper 💻 Code Stars

🛠️ Projects

microsoft/RD-Agent Project
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI.
Python
Star   – Fork   –
microsoft/qlib Project
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with RD-Agent to automate R&D process.
Python
Star  – Fork  –
LLMQuant/quant-wiki Project
A comprehensive wiki for quantitative finance and AI in finance, covering strategies, models, and best practices.
Markdown
Star  – Fork  –
TongjiFinLab/awesome-time-series-forecasting Awesome List
A curated list of papers, datasets, and resources for time series forecasting
Markdown
Star  – Fork  –
TongjiFinLab/FinTSB Benchmark
FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting.
Python
Star  – Fork  –
ulab-uiuc/live-trade-bench Benchmark
Live Trading Benchmark: A comprehensive evaluation framework for real-world trading strategies and algorithms.
Python
Star  – Fork  –

📖 Educations

Aug, 2025 - May, 2027 (expected)
Master of Science in Intelligent Information Systems @ School of Computer Science, Carnegie Mellon University
Sept, 2021 - Jun, 2025
Bachelor in Computer Science and Technology @ Tongji University

🏆 Awards

2026.07My paper was awarded the Oral Paper Award at the SIGKDD 2026 Workshop on Machine Learning in Finance.
2026.06Represented the CMU team and won 1st place among OpenAI-sponsored teams in the Grounded Reasoning Cup organized by Databricks, and received a $10,000 prize.
2026.06My paper was awarded the Spotlight Paper Award at ICML 2026.
2025.10My paper was awarded the Best Paper Award at the ICAIF 2025 Workshop.
2025.08Certificate of MSR Asia Stars of Tomorrow Internship Program (Highest honor for interns, awarded to the Top 1%).
2025.06Top Honors for the Graduation Thesis (Top 0.2%) at Tongji University.
2024.12My paper was awarded the Excellent Paper Award at ICFOD 2024.
2024.11Certificate of Outstanding Poster Presentation at the Microsoft Research Asia Intern Tech Fest.
2024.09Certificate of Valuable Presentation at the Microsoft Research Asia Intern Tech Talk Series.
2024Tongji University Industrial Bank Scholarship (awarded to only two students).
2023Tongji University First-Class Scholarship (Top 5%).
2023Tongji University Social Activity Scholarship.
2022Tongji University Second-Class Scholarship (Top 10%).

🤝 Service

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