About me
Hi! I’m Weiqi (Vicky) Wu, a first year graduate student majored in computer science at School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University.
My research interests are about natural language processing and knowledge graph, including knowledge probing, information extraction and KG-based recommendation system. Through all my research projects and participation in workshops, contests and conferences, I have gained invaluable knowledge and committed to continuous exploration in these evolving fields.
[LATEST] My new work about LLM-based interactive drama is accepted at ACL 2024 Findings. See you in Bangkok!
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
Publications
* Denotes Equal Contribution.
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.
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)
- Haoyi Wu, Wenyang Hui, Yezeng Chen, Weiqi Wu, Kewei Tu, and Yi Zhou, “Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset”. In Findings of EMNLP, 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.