Hi! I’m Weiqi (Vicky) Wu. I am currently a Research Engineer at ByteDance Seed, working on LLM post-training. I received my M.E. in Computer Science and Technology from Shanghai Jiao Tong University, where I was advised by Prof. Hai Zhao.

My interests lie in large language models and agents, particularly post-training, reinforcement learning, reasoning, agentic search, and role-playing agents. My work has been published at ACL / EMNLP / NAACL, and my first-author paper received the ACL 2023 Outstanding Paper Award 🏆.

I am always happy to connect with researchers and developers working on the next generation of LLMs and agents. Let’s connect on LinkedIn →

Work Experience

ByteDance Seed

December 2025 – Present

Full-time · LLM Post-training

Working on post-training large language models and agents, with a focus on reinforcement learning, reward modeling, agentic capabilities, and global applications.

ByteDance

April 2025 – November 2025

Research Intern · AI Recommendation

Worked on personalized conversation recommendation and long-term memory modeling for DouBao as part of the Jin Dou Yun talent program.

Alibaba Tongyi Lab

June 2024 – April 2025

Research Intern · NLP & DeepResearch

Worked on deep research agents and open-domain retrieval-augmented generation.

Microsoft Research Asia

July 2021 – October 2021

Research Intern · NLP

Worked on natural language processing and news recommendation.

Education

Shanghai Jiao Tong University

September 2023 – March 2026

M.E. in Computer Science and Technology

Advised by Prof. Hai Zhao.

ShanghaiTech University

September 2019 – June 2023

B.E. in Computer Science and Technology

Advised by Prof. Kewei Tu.

Publications

• 🏆 Outstanding Paper Award · [ACL 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, Toronto, Canada, July 9-14, 2023. [GitHub]
• 🗣 Oral Presentation · [ACL 2026 Industry] Hongwei Zheng*, Weiqi Wu*, Zhengjia Wang, Guanyu Jiang, Haoming Li, Tianyu Wu, Yongchun Zhu, Jingwu Chen, and Feng Zhang, “IceBreaker for Conversational Agents: Breaking the First-Message Barrier with Personalized Starters”. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics, San Diego, California, USA, 2026.
• [ACL 2025] Weiqi Wu, Hongqiu Wu, Hai Zhao, “X-Turing: Towards an Enhanced and Efficient Turing Test for Long-Term Dialogue Agents”. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, Vienna, Austria, 2025.
• [NAACL 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”. In the Findings of the Association for Computational Linguistics: NAACL 2025. [GitHub]
• Weiqi Wu*, Xin Guan*, Shen Huang, Yong Jiang, Pengjun Xie, Fei Huang, Jiuxin Cao, Hai Zhao, Jingren Zhou, “MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability”. [GitHub]
• [ACL 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, Bangkok, Thailand, August 11-16, 2024. [GitHub]
• [ACL 2025] Hongqiu Wu, Weiqi Wu, Tianyang Xu, Jiameng Zhang, Hai Zhao, “Towards Enhanced Immersion and Agency for LLM-based Interactive Drama”. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, Vienna, Austria, 2025. [GitHub]
• [EMNLP 2025 Demo] Tianyang Xu*, Hongqiu Wu*, Weiqi Wu, Hai Zhao. “Open-Theatre: An Open-Source Toolkit for LLM-based Interactive Drama”
• [EACL 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, May 2–6, 2023.
• [EMNLP 2022] 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, December 7–11, 2022.
• [EMNLP 2025] 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”. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025. [GitHub]
• [EMNLP 2023] 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, 2023.
• Hongqiu Wu, Zekai Xu, Tianyang Xu, Jiale Hong, Weiqi Wu, Hai Zhao, Min Zhang, Zhezhi He, “Scaling Virtual World with Delta-Engine”.

* Denotes Equal Contribution.

Awards

• ACL 2023 Outstanding Paper
• IndySCC (Student SuperComputing) 2022 Champion
• National Scholarship 2025
• Principal Award of ShanghaiTech University
• Second Prize of the Contemporary Undergraduate Mathematical Contest in Modeling (CUMCM)
• BYD Scholarship 2024

Miscellaneous

• Beyond academia, I am a member of the Jiangsu Writers’ Association. I have a long-standing interest in reading and writing prose poetry, with a particular appreciation for modern Chinese poetry. My favourite poets include Zhang Zao and Hai Zi.
• Although not being athletic, I am an avid follower of competitive sports like Formula 1. I support Red Bull Racing and Max Verstappen. That is, No Risk, Full Push!