---
title: "Ercong Nie — author profile and papers — Elamur Research"
description: "Ercong Nie, Shanghai Jiao Tong University: 7 papers on Elamur Research (2025–2026), h-index 3 — affiliations, topics, co-authors and who…"
canonical: "https://research.elamur.ai/free/en/authors/ercong-nie/"
---
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# Ercong Nie

Ercong Nie has 7 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Multilingual & cross-lingual NLP](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/); often with [Hinrich Schuetze](https://md.research.elamur.ai/free/en/authors/hinrich-schuetze/), [Mingyang Wang](https://md.research.elamur.ai/free/en/authors/mingyang-wang/), [Daling Wang](https://md.research.elamur.ai/free/en/authors/daling-wang/).

7 papers in our library · 2025–2026

[OpenAlex](https://openalex.org/A5054893267) · [ORCID](https://orcid.org/0000-0003-1453-4460) · [**h-index 3**](https://openalex.org/authors/A5054893267) · [83 works](https://openalex.org/works?filter=author.id:A5054893267) · [67 citations](https://openalex.org/works?filter=author.id:A5054893267&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 7 works in our library](https://md.research.elamur.ai/free/en/authors/ercong-nie/#papers) · [🔗 Cited 93 times in our library](https://md.research.elamur.ai/free/en/authors/ercong-nie/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6791](https://md.research.elamur.ai/free/en/paper-stars/page/68/#star-6791)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Ercong+Nie) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ercong+Nie) · [dblp](https://dblp.org/search?q=Ercong+Nie) · [ACL Anthology](https://aclanthology.org/search/?q=Ercong+Nie)

## Affiliations

[🎓**Ludwig-Maximilians-Universität München** Munich · Germany 2022–2026 · 55 papersEmployment 2022–2026 · PhD Candidate, Centre for Information and Language Processing*current*](https://md.research.elamur.ai/free/en/universities/ludwig-maximilians-universitat-munchen/) · [🎓**Munich Center for Machine Learning** Munich · Germany 2023–2026 · 37 papers*current*](https://md.research.elamur.ai/free/en/universities/munich-center-for-machine-learning/) · [🎓**Shanghai Jiao Tong University** Shanghai · China 2026 · 7 papersEmployment since 2026 · Assistant Professor, School of Foreign Languages*current*](https://md.research.elamur.ai/free/en/universities/shanghai-jiao-tong-university/) · [🏥**LMU Klinikum** Munich · Germany 2026 · 1 paper*current*](https://ror.org/02jet3w32) · [🎓**Technische Universität Darmstadt** Darmstadt · Germany 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/technische-universitat-darmstadt/) · [🎓**Karlsruhe Institute of Technology** Karlsruhe · Germany 2024 · 2 papers](https://md.research.elamur.ai/free/en/universities/karlsruhe-institute-of-technology/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 7 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 7 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Philosophy · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/philosophy/)

🧭 Topics 5 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Multilingual & cross-lingual NLP · 2 works](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Interpretability · 1 work](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/)

## Works by year

### 2020s

[**2026** 5 papers](https://md.research.elamur.ai/free/en/authors/ercong-nie/year/2026/) · [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/ercong-nie/year/2025/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yan-2026-memory-r1-enhancing-large-language/)** *(2026 · 49 citations)* LLMs lose information that falls outside their context window. Systems that add an external memory bank usually depend on fixed heuristics or prompted LLMs to choose what to store and retrieve, and nothing in that choice is trained against answer correctness. Memory-R1 addresses this with reinforcement learning…
2. **[Lost in Multilinguality: Dissecting Cross-lingual Factual Inconsistency in Transformer Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-lost-multilinguality-dissecting-cross-lingual/)** *(2025 · 31 citations)* Multilingual language models often answer a factual question correctly in one language but wrongly when the same question is posed in another.
3. **[BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning](https://md.research.elamur.ai/free/en/papers/nie-2025-bmike-53-investigating-cross-lingual/)** *(2025 · 12 citations)* Knowledge editing (KE) updates facts stored in large language models without retraining. Most gradient-free work is monolingual, and it is unclear whether an edit made in English carries over to questions asked in other languages. The authors build BMIKE-53, a benchmark for cross-lingual in-context knowledge editing…
4. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/)** *(2026 · 9 citations)* Most earlier reviews of mechanistic interpretability (MI) in LLMs describe what researchers have discovered inside models.
5. **[PlaM: Training-Free Plateau-Guided Model Merging for Better Visual Grounding in MLLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plam-training-free-plateau-guided/)** *(2026 · 1 citation)* Multimodal instruction fine-tuning tends to weaken the text reasoning that MLLMs inherit from their base language models.
6. **[Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-look-within-or-beyond-theoretical/)** *(2026)* Parameter-efficient fine-tuning (PEFT) methods such as LoRA often match full fine-tuning (FFT) on standard benchmarks. It is less clear whether they hold up on harder tasks like reasoning and instruction-following, or under adversarial inputs. The authors address this with a theoretical analysis backed by experiments.
7. **[SAD: A Large-Scale Strategic Argumentative Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/liu-2026-sad-large-scale-strategic-argumentative/)** *(2026)* Most argument-generation corpora treat argumentation as a one-shot task: produce an argument for a topic or rebut a single claim.

## All works

8 works of theirs in our library, the most cited first; 7 with a page here, the others link their original until we summarise them.

1. **[Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yan-2026-memory-r1-enhancing-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sikuan Yan, Xiufeng Yang, Zuchao Huang, et al.*2026 · 49 citations*
2. **[Lost in Multilinguality: Dissecting Cross-lingual Factual Inconsistency in Transformer Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-lost-multilinguality-dissecting-cross-lingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyang Wang, Heike Adel, Lukas Lange, et al.*2025 · 31 citations*
3. **[BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning](https://md.research.elamur.ai/free/en/papers/nie-2025-bmike-53-investigating-cross-lingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ercong Nie, Bo Shao, Mingyang Wang, et al.*2025 · 12 citations*
4. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations*
5. **[Cross-Lingual Constituency Parsing for Middle High German: A Delexicalized Approach ↗](https://aclanthology.org/2023.alp-1.8/) Proceedings of the Ancient Language Processing Workshop · no summary yet**Ercong Nie, Helmut Schmid, Hinrich Schütze*2023 · 3 citations*
6. **[PlaM: Training-Free Plateau-Guided Model Merging for Better Visual Grounding in MLLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plam-training-free-plateau-guided/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijing Wang, YongKang Liu, Mingyang Wang, et al.*2026 · 1 citation*
7. **[Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-look-within-or-beyond-theoretical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Xingle Xu, Ercong Nie, et al.*2026*
8. **[SAD: A Large-Scale Strategic Argumentative Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/liu-2026-sad-large-scale-strategic-argumentative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Jiayang Yu, Mingyang Wang, et al.*2026*

## Co-authors here

12 of 33 co-authors with a page, the most papers together first.

- [Hinrich Schuetze](https://md.research.elamur.ai/free/en/authors/hinrich-schuetze/) ×6
- [Mingyang Wang](https://md.research.elamur.ai/free/en/authors/mingyang-wang/) ×5
- [Daling Wang](https://md.research.elamur.ai/free/en/authors/daling-wang/) ×3
- [Shi Feng](https://md.research.elamur.ai/free/en/authors/shi-feng/) ×3
- [YongKang Liu](https://md.research.elamur.ai/free/en/authors/yongkang-liu/) ×3
- [Zifeng Ding](https://md.research.elamur.ai/free/en/authors/zifeng-ding/) ×2
- [Zijing Wang](https://md.research.elamur.ai/free/en/authors/zijing-wang/) ×2
- [Chenming Shang](https://md.research.elamur.ai/free/en/authors/chenming-shang/)
- [Heike Adel](https://md.research.elamur.ai/free/en/authors/heike-adel/)
- [Helmut Schmid](https://md.research.elamur.ai/free/en/authors/helmut-schmid/)
- [Hengyuan Zhang](https://md.research.elamur.ai/free/en/authors/hengyuan-zhang/)
- [Jannik Strötgen](https://md.research.elamur.ai/free/en/authors/jannik-strotgen/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×5: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×3, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) ×2
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2
- Proceedings of the Ancient Language Processing Workshop

## Cited by

Papers of our library cite their works 93 times (of the 149,439 papers whose bibliographies we read); [28 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ercong-nie/cited-by/).

Updated 1 November 2026