GAIR, SII 2024.9-Now
TsinghuaC3I, Tsinghua University, 2022.9 - 2024.9
Zheng, Y.*, Fu, D.*, Hu, X.*, Cai, X., Ye, L., Lu, P., & Liu, P. (2024). DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments. arXiv preprint arXiv:2504.03160.
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).
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.
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.
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).
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.
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).
Talk at Bytedance,
Reviewer for
ICLR 2025
ACL ARR 2024 June, August, October, December
ACL ARR 2025 February