CV

Education

• M.S. in Dept. of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), 2023.9 - Now
• B.S. in Dept. of Electronic Engineering, Beijing University of Posts and Telecommunications (BUPT), 2019.9 - 2023.6

Work experience

• 2024: Intern at Meituan
  • Data Synthesis
  • Reinforcement learning

Visiting

• GAIR, SII 2024.9-Now

• TsinghuaC3I, Tsinghua University, 2022.9 - 2024.9

Skills

• Coding in C++/Python
• Familiar with:
  • Verl
  • ray
  • LLaMA-Factory
  • Deepspeed

Publications

DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments

Zheng, Y.*, Fu, D.*, Hu, X.*, Cai, X., Ye, L., Lu, P., & Liu, P. (2025). DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP).

AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Fu, D., He, K., Wang, Y., Hong, W., Gongque, Z., Zeng, W., Wang, W., Wang, J., Cai, X., & Xu, W. (2025). AgentRefine: Enhancing Agent Generalization through Refinement Tuning. In International Conference on Learning Representations (ICLR 2025).

MSI-Agent: Incorporating Multi-Scale Insight into Embodied Agents for Superior Planning and Decision-Making

Fu, D., Qi, B., Gao, Y., Jiang, C., Dong, G., & Zhou, B. (2024). MSI-Agent: Incorporating Multi-Scale Insight into Embodied Agents for Superior Planning and Decision-Making. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing.

How Do Your Code LLMs Perform? Empowering Code Instruction Tuning with High-Quality Data

Wang, Y.*, He, K.*, Fu, D.*, Gongque, Z., Xu, H., Chen, Y., Wang, Z., Fu, Y., Dong, G., Diao, M., Wang, J., Zhang, M., Cai, X., & Xu, W. (2024). How Do Your Code LLMs Perform? Empowering Code Instruction Tuning with High-Quality Data. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing.

CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery

Song, X., Diao, M., Dong, G., Wang, Z., Fu, Y., Qiao, R., Wang, Z., Fu, D., Wu, H., Liang, B., Zeng, W., Wang, Y., GongQue, Z., Yu, J., Tan, Q., & Xu, W. (2025). CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery. In International Conference on Learning Representations (ICLR 2025).

On Large Language Models’ Hallucination with Regard to Known Facts

Jiang, C., Qi, B., Hong, X., Fu, D., Cheng, Y., Meng, F., Yu, M., Zhou, B., & Zhou, J. (2024). On Large Language Models' Hallucination with Regard to Known Facts. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics.

PreAct: Prediction Enhances Agent’s Planning Ability

Fu, D., Huang, J., Lu, S., Dong, G., Wang, Y., He, K., & Xu, W. (2025). PreAct: Prediction Enhances Agent's Planning Ability. In Proceedings of the 2025 International Conference on Computational Linguistics (COLING 2025).

Talks

MSI-Agent Talk

December 03, 2024

Talk at Bytedance,

Service and leadership

Reviewer for

• ICLR 2025

• ACL ARR 2024 June, August, October, December

• ACL ARR 2025 February