Hi! I’m Weiqi (Vicky) Wu, a second year graduate student majored in computer science at School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University. I’m advised by Prof. Hai Zhao.

My research interests are about natural language processing and knowledge graph, including Agent, RAG, Role-playing LLMs and Knowledge Probing. I’m also serving as reviewer for ACL Rolling Review.

I’m currently working as a Research Intern at Alibaba TongYi Lab, focusing on open-domain RAG and reasoning agents. I will graduate in March 2026 and am actively seeking summer internship as well as fall recruitment opportunities related to LLMs!

Education

• M.E. in Computer Science and Technology, Shanghai Jiao Tong University, 2023.09-2026.03 (estimated)

• B.E. in Computer Science and Technology, ShanghaiTech University, 2019.09-2023.06

  • Sharing: Graduate Stories｜Weiqi Wu: Life is a wildness, not a track

Publications

2025

• Weiqi Wu, Shen Huang, Yong Jiang, Pengjun Xie, Fei Huang, Hai Zhao, “Unfolding the Headline: Iterative Self-Questioning for News Retrieval and Timeline Summarization” (NAACL 2025 Findings). [GitHub]
• Hongqiu Wu, Weiqi Wu, Tianyang Xu, Jiameng Zhang, Hai Zhao, “Towards Enhanced Immersion and Agency for LLM-based Interactive Drama”.
• Qiuchen Wang, Ruixue Ding, Zehui Chen, Weiqi Wu, Shihang Wang, Pengjun Xie, Feng Zhao, “ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents”.

2024

• Weiqi Wu*, Hongqiu Wu*, Lai Jiang, Xingyuan Liu, Jiale Hong, Hai Zhao, Min Zhang, “From Role-Play to Drama-Interaction: An LLM Solution” In the Findings of 62th Annual Meeting of the Association for Computational Linguistics (ACL 2024 Findings), Bangkok, Thailand, August 11-16, 2024. [GitHub]
• Weiqi Wu, Hongqiu Wu, Hai Zhao, “Self-Directed Turing Test for Large Language Models”.
• Hongqiu Wu, Zekai Xu, Tianyang Xu, Jiale Hong, Weiqi Wu, Hai Zhao, Min Zhang, Zhezhi He, “Scaling Virtual World with Delta-Engine”.

2023

• Weiqi Wu, Chengyue Jiang, Yong Jiang, Pengjun Xie and Kewei Tu, “Do PLMs Know and Understand Ontological Knowledge?”. In the 61th Annual Meeting of the Association for Computational Linguistics (ACL 2023), Toronto, Canada, July 9-14, 2023. **(Outstanding Paper Award) **[GitHub]
• Haoyi Wu, Wenyang Hui, Yezeng Chen, Weiqi Wu, Kewei Tu, and Yi Zhou, “Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset”. In the Findings of 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023 Findings), 2023.
• Chengyue Jiang, Yong Jiang, Weiqi Wu, Yuting Zheng, Pengjun Xie, and Kewei Tu, “COMBO: A Complete Benchmark for Open KG Canonicalization”. In the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), May 2–6, 2023.
• Chengyue Jiang, Yong Jiang, Weiqi Wu, Pengjun Xie, and Kewei Tu, “Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field”. In the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), December 7–11, 2022.

* Denotes Equal Contribution.

Awards

• ACL 2023 Outstanding Paper
• IndySCC (Student SuperComputing) 2022 Champion
• Principal Award of ShanghaiTech University
• Second Prize of Contemporary Undergraduate Mathematical Contest in Modeling (CUMCM)
• 2024 BYD Scholarship