PhD
Chair of Computational Linguistics at LMU
Centrum für Informations- und Sprachverarbeitung
Oettingenstraße 67, 1. OG, Flügel C
D-80538 München
Biosketch
Shengqiang is a first-year Ph.D. student at the Center for Information and Language Processing at LMU Munich. He is very fortunately co-advised by Prof. Hinrich Schütze and Prof. Barbara Plank. Previously, he obtained my master’s degree from Peking University in July 2021. Shengqiang spent a gap year as a research assistant advised by Wei Lu at SUTD, Singapore. He made several internships in industries such as Microsoft Research Asia and Baidu Search.
relAI Research
Exploring Long-Horizon Embodied Instruction Following with Foundation Models
I am interested in developing better embodied agents that are good at long-horizon instruction following tasks with foundation models. More specifically, I build the corresponding benchmarks and datasets for evaluating the long-horizon instruction following capabilities, such as the work LoHoRavens [1], and also design models with better long-horizon reasoning and decision-making capabilities.
[1] Zhang, Shengqiang, et al. “Lohoravens: A long-horizon language-conditioned benchmark for robotic tabletop manipulation.” arXiv preprint arXiv:2310.12020 (2023).