Cheng Qian

Cheng Qian is a PhD student at UIUC, advised by Prof. Heng Ji. His current research focuses on LLM agent its tool use, reasoning, alignment, and creativity. Before joining UIUC, he has also worked with Prof. Sherry Wu and Prof. Chenyan Xiong from CMU on LLM knowledge and tool use. He finished his Bachelor's degree at Tsinghua University, advised by Prof. Zhiyuan Liu.

News & Updates

  • [2025/10] We have released the technical report on xRouter, a LLM orchestration framework for effective and efficient query routing.
  • [2025/10] See our UserRL work featured on social media including Twitter and WeChat! I am also going to give several talks on user-centric agent design and evaluation. See you online!
  • [2025/09] My series of works at Salesforce AI Research on LLM agent for user alignment is coming! Check out the UserRL paper which builds upon and expands our previous UserBench paper. We also released our code for all gym environments and training here.
  • [2025/09] Our ToolRL paper is accepted by NeurIPS 2025! Thanks to all the collaborators! Hope to see you all at San Diego this December!
  • [2025/08] I have five first-suthor and co-author works accepted by EMNLP 2025, including the ModelingAgent paper. Congratulations to all the authors! Hope to see you all at Su Zhou this November!
  • [2025/05] Glad to announce that I am joining Salesforce AI Research for my 2025 summer internship!
  • [2025/05] My newest paper on how to design agent for math modeling is released! Check the ModelingAgent paper to see how to ground math in real world problem solving.
  • [2025/05] Glad to announce that I have six first-author and co-author works accepted by ACL 2025. My work EscapeAgent is accepted in the main track. Congratulations to all the authors!
  • [2025/04] We released our ToolRL paper, which focuses on the reward shaping for LLM tool use tasks. We also released our code here. Check it out for more details!
  • [2025/04] I am at NAACL 2025 this year at New Mexico! Hope to chat with you there!
  • [2025/03] We released the SMART paper which for the first time systematically evaluates the tool overuse problem in LLM and LLM-driven agent.
  • [2024/12] My first paper in PhD is out! Check the EscapeBench paper to see if your LLM is creative enough to escape from the sandbox environment!
  • [2024/12] I am participating in EMNLP 2024 at Miami this year! Hope to see everyone!
  • [2024/12] Graduated from Tsinghua, I am now starting my PhD at UIUC! Looking forward to working with you all!

Research Focus

My research focuses on transforming large language models (LLMs) into truly autonomous agents that operate reliably in dynamic, ambiguous real-world settings. While today's LLMs excel at analytical reasoning when problems are well-formed and knowledge is encoded in their parameters, they struggle when tasks demand up-to-date information, adaptive behavior, or nuanced understanding of human intent. I envision agents that combine internal reasoning with external tool use (e.g., search, calculators, APIs) to pursue goals, incorporate feedback, and improve over time—moving beyond static models toward systems that learn continuously.

To guide this evolution, I propose the Lifelong Agent framework, which characterizes agentic intelligence as an iterative cycle of Learn, Align, and Evolve. Learn equips agents to acquire, organize, and apply knowledge for creativity and efficiency; Align adapts behavior to environment- and user-specific preferences, goals, and constraints; and Evolve drives sustained self-improvement via memory, reflection, and feedback across tasks and environments. My work integrates three tightly coupled threads at each phase—analysis (diagnosing agent behavior), training (designing methods that enhance capabilities), and application (deploying agents to solve real-world problems). This agenda aims to produce scalable, tool-using agents that continually adapt, remain aligned with human values, and deliver robust, practical impact.

Research Framework: Illustration of Lifelong Agent

Research Framework: Illustration of Lifelong Agent and corresponding research efforts.

Publications ( show selected / show all by date / show all by topic )

Topics: Agent Learning / Agent Alignment / Agent Evolution / Agent Evaluation
Past topics: LLM Pre-training / LLM Knowledge / LLM Analysis / LLM Post-training (*/†: indicates equal contribution.)

Exploring Mode Connectivity for Pre-trained Language Models
Yujia Qin*, Cheng Qian*, Jing Yi*, Weize Chen, Yankai Lin, Xu Han, Zhiyuan Liu, Maosong Sun, Jie Zhou

EMNLP 2022 (Main Track) Paper / Code

Tool Learning with Foundation Models
Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Yufei Huang, Chaojun Xiao, Chi Han, Yi Ren Fung, Yusheng Su, Huadong Wang, Cheng Qian, Runchu Tian, Kunlun Zhu, Shihao Liang, Xingyu Shen, Bokai Xu, Zhen Zhang, Yining Ye, Bowen Li, Ziwei Tang, Jing Yi, Yuzhang Zhu, Zhenning Dai, Lan Yan, Xin Cong, Yaxi Lu, Weilin Zhao, Yuxiang Huang, Junxi Yan, Xu Han, Xian Sun, Dahai Li, Jason Phang, Cheng Yang, Tongshuang Wu, Heng Ji, Zhiyuan Liu, Maosong Sun

ACM Computing Surveys / Paper / ACM

Recyclable Tuning for Continual Pre-training
Yujia Qin*, Cheng Qian*, Xu Han, Yankai Lin, Huadong Wang, Ruobing Xie, Zhiyuan Liu, Maosong Sun, Jie Zhou

ACL 2023 Findings / Paper / Code

CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models
Cheng Qian, Chi Han, Yi Fung, Yujia Qin, Zhiyuan Liu, Heng Ji

EMNLP 2023 Findings / Paper / Code

Toolink: Linking Toolkit Creation and Using through Chain-of-Solving on Open-Source Model
Cheng Qian, Chenyan Xiong, Zhenghao Liu, Zhiyuan Liu

NAACL 2024 (Main Track) Paper / Code

Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agents
Cheng Qian*, Bingxiang He*, Zhong Zhuang, Jia Deng, Yujia Qin, Xin Cong, Zhong Zhang, Jie Zhou, Yankai Lin, Zhiyuan Liu, Maosong Sun

ACL 2024 (Main Track) Paper / Code / Dataset / Model /

Investigate-Consolidate-Exploit: A General Strategy for Inter-Task Agent Self-Evolution
Cheng Qian*, Shihao Liang*, Yujia Qin, Yining Ye, Xin Cong, Yankai Lin, Yesai Wu, Zhiyuan Liu, Maosong Sun

ArXiv Preprint / Paper

"Merge Conflicts!" Exploring the Impacts of External Distractors to Parametric Knowledge Graphs
Cheng Qian, Xinran Zhao, Sherry Tongshuang Wu

COLM 2024 / Paper / Code

Aligning LLMs with Individual Preferences via Interaction
Shujin Wu, May Fung, Cheng Qian, Jeonghwan Kim, Dilek Hakkani-Tür, Heng Ji

COLING 2025 / Paper / Code

Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance
Yaxi Lu, Shenzhi Yang, Cheng Qian, Guirong Chen, Qinyu Luo, Yesai Wu, Huadong Wang, Xin Cong, Zhong Zhang, Yankai Lin, Weiwen Liu, Yasheng Wang, Zhiyuan Liu, Fangming Liu, Maosong Sun

ICLR 2025 / Paper / Code

Distance between Relevant Information Pieces Causes Bias in Long-Context LLMs
Runchu Tian, Yanghao Li, Yuepeng Fu, Siyang Deng, Qinyu Luo, Cheng Qian, Shuo Wang, Xin Cong, Zhong Zhang, Yesai Wu, Yankai Lin, Huadong Wang, Xiaojiang Liu

ACL 2025 Findings / Paper

EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents
Rui Yang*, Hanyang Chen*, Junyu Zhang*, Mark Zhao*, Cheng Qian, Kangrui Wang, Qineng Wang, Teja Venkat Koripella, Marziyeh Movahedi, Manling Li, Huan Zhang, Tong Zhang

ICML 2025 / Paper / Website and Code

SMART: Self-Aware Agent for Tool Overuse Mitigation
Cheng Qian*, Emre Can Acikgoz*, Hongru Wang, Xiusi Chen, Avirup Sil, Dilek Hakkani-Tür, Gokhan Tur, Heng Ji

ACL 2025 Findings / Paper / Code

The Law of Knowledge Overshadowing: Towards Understanding, Predicting, and Preventing LLM Hallucination
Yuji Zhang, Sha Li, Cheng Qian, Jiateng Liu, Pengfei Yu, Chi Han, Yi R. Fung, Kathleen McKeown, Chengxiang Zhai, Manling Li, Heng Ji

ACL 2025 Findings / Paper

MultiAgentBench: Evaluating the Collaboration and Competition of LLM Agents
Kunlun Zhu*, Hongyi Du*, Zhaochen Hong*, Xiaocheng Yang*, Shuyi Guo*, Zhe Wang*, Zhenhailong Wang, Cheng Qian, Xiangru Tang, Heng Ji, Jiaxuan You

ACL 2025 (Main Track) Paper / Code

AIR: A Systematic Analysis of Annotations, Instructions, and Response Pairs in Preference Dataset
Bingxiang He*, Wenbin Zhang*, Jiaxi Song, Cheng Qian, Zixuan Fu, Bowen Sun, Ning Ding, Haiwen Hong, Longtao Huang, Hui Xue, Ganqu Cui, Wanxiang Che, Zhiyuan Liu, Maosong Sun

COLM 2025 / Paper

RM-R1: Reward Modeling as Reasoning
Xiusi Chen*, Gaotang Li*, Ziqi Wang*, Bowen Jin, Cheng Qian, Yu Wang, Hongru Wang, Yu Zhang, Denghui Zhang, Tong Zhang, Hanghang Tong, Heng Ji

ArXiv Preprint / Paper / Code

ToolRL: Reward is All Tool Learning Needs
Cheng Qian, Emre Can Acikgoz, Qi He, Hongru Wang, Xiusi Chen, Dilek Hakkani-Tür, Gokhan Tur, Heng Ji

NeurIPS 2025 / Paper / Code

DecisionFlow: Advancing Large Language Model as Principled Decision Maker
Xiusi Chen, Shanyong Wang, Cheng Qian, Hongru Wang, Peixuan Han, Heng Ji

Findings of EMNLP 2025 (Findings) / Paper Code

SafeSwitch: Steering Unsafe LLM Behavior via Internal Activation Signals
Peixuan Han*, Cheng Qian*, Xiusi Chen, Yuji Zhang, Denghui Zhang, Heng Ji

EMNLP 2025 Findings / Paper / Code

The Right Time Matters: Data Arrangement Affects Zero-Shot Generalization in Instruction Tuning
Bingxiang He*, Ning Ding*, Cheng Qian*, Jia Deng, Ganqu Cui, Lifan Yuan, Haiwen Hong, Huan-ang Gao, Longtao Huang, Hui Xue, and others

ACL 2025 Findings / Paper / Code

EscapeBench: Towards Advancing Creative Intelligence of Language Model Agents
Cheng Qian, Peixuan Han, Qinyu Luo, Bingxiang He, Xiusi Chen, Yuji Zhang, Hongyi Du, Jiarui Yao, Xiaocheng Yang, Denghui Zhang, Yunzhu Li, Heng Ji

ACL 2025 (Main Track) / Paper / Code

Enhancing Open-Domain Task-Solving Capability of LLMs via Autonomous Tool Integration from GitHub
Bohan Lyu, Xin Cong, Heyang Yu, Pan Yang, Cheng Qian, Zihe Wang, Yining Ye, Yaxi Lu, Chen Qian, Yujia Qin, Zhong Zhang, Yukun Yan, Yankai Lin, Zhiyuan Liu, Maosong Sun

ACL 2025 (Main Track) / Paper / Code

A Survey of Self-Evolving Agents: On Path to Artificial Super Intelligence
Huan-ang Gao, Jiayi Geng, Wenyue Hua, Mengkang Hu, Xinzhe Juan, Hongzhang Liu, Shilong Liu, Jiahao Qiu, Xuan Qi, Yiran Wu, Hongru Wang, Han Xiao, Yuhang Zhou, Shaokun Zhang, Jiayi Zhang, Jinyu Xiang, Yixiong Fang, Qiwen Zhao, Dongrui Liu, Qihan Ren, Cheng Qian, Zhenghailong Wang, Minda Hu, Huazheng Wang, Qingyun Wu, Heng Ji, Mengdi Wang

ArXiv Preprint / Paper / Project Repo (Paper List)

UserBench: An Interactive Gym Environment for User-Centric Agents
Cheng Qian, Zuxin Liu, Akshara Prabhakar, Zhiwei Liu, Jianguo Zhang, Haolin Chen, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang

ArXiv Preprint / Paper / Code

UserRL: Training Interactive User-Centric Agent via Reinforcement Learning
Cheng Qian, Zuxin Liu, Akshara Prabhakar, Jielin Qiu, Zhiwei Liu, Haolin Chen, Shirley Kokane, Heng Ji, Weiran Yao, Shelby Heinecke, Silvio Savarese, Caiming Xiong, Huan Wang

ArXiv Preprint / Paper / Code

WINELL: Wikipedia Never-Ending Updating with LLM Agents
Revanth Gangi Reddy, Tanay Dixit, Jiaxin Qin, Cheng Qian, Daniel Lee, Jiawei Han, Kevin Small, Xing Fan, Ruhi Sarikaya, Heng Ji

ArXiv Preprint / Paper / Code

ISACL: Internal State Analyzer for Copyrighted Training Data Leakage
Guangwei Zhang, Qisheng Su, Jiateng Liu, Cheng Qian, Yanzhou Pan, Yanjie Fu, Denghui Zhang

arXiv Preprint / Paper / Code

Toward a Theory of Agents as Tool-Use Decision-Makers
Hongru Wang*, Cheng Qian*, Manling Li, Jiahao Qiu, Boyang Xue, Mengdi Wang, Heng Ji, Kam-Fai Wong

ArXiv Preprint / Paper

Acting Less is Reasoning More! Teaching Model to Act Efficiently
Hongru Wang, Cheng Qian, Wanjun Zhong, Xiusi Chen, Jiahao Qiu, Shijue Huang, Bowen Jin, Mengdi Wang, Kam-Fai Wong, Heng Ji

ArXiv Preprint / Paper

Atomic Reasoning for Scientific Table Claim Verification
Yuji Zhang, Qingyun Wang, Cheng Qian, Jiateng Liu, Chenkai Sun, Denghui Zhang, Tarek Abdelzaher, Chengxiang Zhai, Preslav Nakov, Heng Ji

ArXiv Preprint / Paper / Code

Alice: Proactive Learning with Teacher's Demonstrations for Weak-to-Strong Generalization
Shujin Wu, Cheng Qian, Yi R. Fung, Paul Pu Liang, Heng Ji

ArXiv Preprint / Paper / Code

ModelingAgent: Bridging LLMs and Mathematical Modeling for Real-World Challenges
Cheng Qian, Hongyi Du, Hongru Wang, Xiusi Chen, Yuji Zhang, Avirup Sil, Chengxiang Zhai, Kathleen McKeown, Heng Ji

EMNLP 2025 Findings / Paper / Code

Veri-R1: Toward Precise and Faithful Claim Verification via Online Reinforcement Learning
Qi He, Cheng Qian, Xiusi Chen, Bingxiang He, Yi R. Fung, Heng Ji

ArXiv Preprint / Paper / Code

ShortageSim: Simulating Drug Shortages under Information Asymmetry
Mingxuan Cui*, Yilan Jiang*, Duo Zhou*, Cheng Qian, Yuji Zhang, Qiong Wang

ArXiv Preprint / Paper / Code

A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions
Emre Can Acikgoz, Cheng Qian, Hongru Wang, Vardhan Dongre, Xiusi Chen, Heng Ji, Dilek Hakkani-Tür, Gokhan Tur

ArXiv Preprint / Paper / Project Repo (Paper List)

Invited Talks

  • [2025/05] “Towards Reasoning as Action,” Invited guest lecture at Northwestern University (CS 496 Agent AI), Host: Manling Li
  • [2025/05] “Towards Reasoning as Action,” Invited talk at IBM Research, Host: Avirup Sil
  • [2025/05] “ToolRL: Reward is All Tool Learning Needs,” Invited talk at NICE (NLP Academic Exchange Platform), Host: Hongru Wang
  • [2025/05] “Implicit User Intention Understanding of LLM Agent,” Invited talk at DEFirst Reading Group, Host: Rebecca Salganik
  • [2023/06] “Tool Learning and Tool Creation of LLM,” Invited talk at SenseTime Smart City Group, Host: Hangyu Mao

Awards & Honors

  • Capital One ASKS Research Fellowship, University of Illinois Urbana-Champaign, 2025
  • Comprehensive Excellence Scholarship, Tsinghua University, 2023 & 2021
  • Volunteering & Social Excellence Scholarship, Tsinghua University, 2022
  • Award of Excellent Student Cadre, Tsinghua University, 2021

Professional Service

Area Chair: ACL 2025, EMNLP 2025
Conference Reviewer: ARR (2023–2025), ACL (2023–2024), EMNLP (2023–2024), NAACL (2023–2024), COLM (2024–2025), COLING (2025), NeurIPS (2025), AAAI (2025)