Schuetze NLP Lab, Center for Information and Language Processing (CIS),
Ludwig Maximilians University of Munich (LMU Munich),
Munich Center for Machine Learning (MCML)
Email: ecnie97 at gmail.com
About me
- Hi, I am Ercong, a PhD in Natural Language Processing (NLP) from the Center for Information and Language Processing (CIS) at LMU Munich.
- I was supervised by PD Dr. Helmut Schmid and Prof. Hinrich Schütze at the Schütze Lab, and was also affiliated with the Munich Center for Machine Learning (MCML).
- I received my M.Sc. in Computational Linguistics and Informatics (Computer Science) from LMU Munich.
- Prior to LMU, I completed my undergraduate studies at Shanghai Jiao Tong University (SJTU), majoring in German Studies with a minor in Finance. During my undergraduate studies, I spent one exchange semester at the University of Heidelberg in Comparative German Studies.
Research Interest
My research lies broadly in Natural Language Processing (NLP), with a particular interest in multilingual large language models, interpretability, and human-inspired language modeling. I am especially interested in how LLMs acquire, represent, and deploy linguistic and factual knowledge across languages, how their internal mechanisms relate to cross-lingual generalization and failure, and how such behaviors can be diagnosed and improved through efficient and interpretable methods.
- Multilingual NLP and multilingual LLMs: multilinguality of LLMs (Nie et al., 2025a), cross-lingual transfer (Nie et al., 2023a, Ma et al., 2024, Nie et al., 2025a), and historical language processing (Nie et al., 2023b).
- Interpretability and internal mechanisms of LLMs: mechanistic interpretability (Nie et al., 2025b), multilingual representation analysis, and model behaviors related to language, knowledge, and reasoning.
- Human-inspired NLP: NLP inspired by human language processing (Zhang et al., 2023, Yan et al., 2025), and computational neurolinguistics (He et al., 2024, He et al., 2025a, He et al., 2025b).
- Efficient methods for NLP: prompt-based learning (Nie et al., 2023c, Ma et al., 2023), low-resource learning (Liu et al., 2024), and parameter-efficient fine-tuning (Yuan et al., 2024, Yuan et al., 2025).
Feel free to reach out if you're interested in topics related to NLP, LLMs, and Agentic AI, including multilinguality, interpretability, retrieval- and memory-augmented methods, human-inspired NLP, and their intersections with digital humanities, social sciences, and domain-specific applications.
Selected Publications
Ercong Nie*, Bo Shao*, Zifeng Ding, Mingyang Wang, Helmut Schmid, Hinrich Schütze. Bmike-53: Investigating cross-lingual knowledge editing with in-context learning. In ACL 2025 (oral). [Paper]
Ercong Nie, Helmut Schmid, Hinrich Schütze. Mechanistic Understanding and Mitigation of Language Confusion in English-Centric Large Language Models. In EMNLP 2025 Findings. [Paper]
Ercong Nie*, Sheng Liang*, Helmut Schmid, Hinrich Schütze. Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages. In ACL Findings 2023. [Paper], [Code]
Ercong Nie, Helmut Schmid, Hinrich Schuetze. Unleashing the Multilingual Encoder Potential: Boosting Zero-Shot Performance via Probability Calibration. In EMNLP Findings 2023. [Paper], [Code]
Ercong Nie, Shuzhou Yuan, Bolei Ma, Helmut Schmid, Michael Färber, Frauke Kreuter, Hinrich Schütze. Decomposed prompting: Unveiling multilingual linguistic structure knowledge in english-centric large language models. In IJCNLP-AACL 2025 Findings. [Paper]
Shuzhou Yuan, Ercong Nie, Michael Färber, Helmut Schmid, Hinrich Schuetze. GNNavi: Navigating the Information Flow in Large Language Models by Graph Neural Network. In ACL Findings 2024. [Paper], [Code]
Bolei Ma*, Ercong Nie*, Shuzhou Yuan, Helmut Schmid, Michael Färber, Frauke Kreuter, Hinrich Schuetze. ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling Tasks. In EACL 2024 (oral). [Paper], [Code]
(* denotes equal contribution)
See more in my publications.
Academic Roles
Service Roles
- Area Chair (AC): ACL 2026
- Program Chair: ICLR 2026 Workshop MemAgents
Reviewer
I regularly review for major NLP conferences and leading AI/ML venues, as well as SCI/SSCI-indexed international journals in NLP, AI, and related interdisciplinary fields.
- Conferences: ICML, ACL, EMNLP, NAACL, COLING, EACL, LREC, IJCNN, etc.
- Journals: IEEE TNNLS, ACM TIST, ACM TALLIP, Royal Society Open Science, Acta Psychologica, Journal of Computational Social Science.
Community Members
- Committee member of NICE, an NLP and AI Academic Exchange Platform.
- Member of AI Grid, a German AI community connecting young AI scientists funded by the German Federal Ministry of Education and Research.
- Junior member of Munich Center for Machine Learning (MCML), one of six German national AI Competence Centers.
- Member of NLP/CL communities such as ACL, GSCL (German Society for Computational Linguistics and Language Technology)
Credits: This page was originally created by Peiqin Lin and has been adopted and modified by me.
