---
title: "Yingji Li — author profile and papers — Elamur Research"
description: "Yingji Li, Ministry of Education of the People's Republic of China: 2 papers on Elamur Research (2026), h-index 8 — affiliations, topics…"
canonical: "https://research.elamur.ai/free/en/authors/yingji-li/"
---
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# Yingji Li

Yingji Li has 2 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Hao Xu](https://md.research.elamur.ai/free/en/authors/hao-xu/), [Rui Song](https://md.research.elamur.ai/free/en/authors/rui-song/), [Fausto Giunchiglia](https://md.research.elamur.ai/free/en/authors/fausto-giunchiglia/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5004425429) · [ORCID](https://orcid.org/0000-0002-3575-1395) · [Wikidata](https://www.wikidata.org/wiki/Q131128374) · [**h-index 8**](https://openalex.org/authors/A5004425429) · [46 works](https://openalex.org/works?filter=author.id:A5004425429) · [175 citations](https://openalex.org/works?filter=author.id:A5004425429&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yingji-li/#papers) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #12309](https://md.research.elamur.ai/free/en/paper-stars/page/124/#star-12309)

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=Yingji+Li) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yingji+Li) · [dblp](https://dblp.org/search?q=Yingji+Li) · [ACL Anthology](https://aclanthology.org/search/?q=Yingji+Li)

## Affiliations

[🎓**Jilin University** Changchun · China 2023–2026 · 27 papersEmployment*current*](https://md.research.elamur.ai/free/en/universities/jilin-university/) · [🔬**Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University** Changchun Shi · China 2024–2026 · 5 papers*current*](https://md.research.elamur.ai/free/en/labs/key-laboratory-of-symbolic-computation-and-knowledge-engineering-of-ministry-of/) · [🏛️**Jilin Province Science and Technology Department** Changchun · China 2026 · 1 paper*current*](https://ror.org/049x38272) · [🏛️**Ministry of Education of the People's Republic of China** Beijing · China 2026 · 1 paper*current*](https://ror.org/01mv9t934) · [🎓**Huaqiao University** Xiamen · China 2025 · 3 papers](https://ror.org/03frdh605) · [🎓**Zhejiang Technical Institute of Economics** Hangzhou · China 2024–2025 · 2 papers](https://ror.org/01e4rvb54)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 8 more institutions on single bylines are not listed.

## Fields, topics and concepts

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

📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/yingji-li/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning](https://md.research.elamur.ai/free/en/papers/song-2026-enhancing-multimodal-large-language-models/)** *(2026)* Large multimodal models are increasingly applied to ancient Chinese scripts, but no one has systematically tested whether they can follow how individual characters changed shape over time.
2. **[From Fake to Real: Mitigating Out-of-Distribution Bias in In-Context Learning via Feedback Supervision from Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-fake-real-mitigating-out-distribution/)** *(2026)* In-context learning (ICL) relies on labeled demonstrations, usually taken from a source dataset. When test data comes from a very different distribution, these demonstrations can mislead the model. In such out-of-distribution (OOD) settings, similarity-based example selection can even do worse than random choice. The…

## All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. **[Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning](https://md.research.elamur.ai/free/en/papers/song-2026-enhancing-multimodal-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Song, Lida Shi, Ruihua Qi, et al.*2026*
2. **[From Fake to Real: Mitigating Out-of-Distribution Bias in In-Context Learning via Feedback Supervision from Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-fake-real-mitigating-out-distribution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Song, Yingji Li, Jian Li, et al.*2026*
3. **[Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval ↗](https://aclanthology.org/2026.acl-long.941/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Hao Xu et al.*2026*

## Co-authors here

4 co-authors with a page, the most papers together first.

- [Hao Xu](https://md.research.elamur.ai/free/en/authors/hao-xu/) ×2
- [Rui Song](https://md.research.elamur.ai/free/en/authors/rui-song/) ×2
- [Fausto Giunchiglia](https://md.research.elamur.ai/free/en/authors/fausto-giunchiglia/)
- [Jian Li](https://md.research.elamur.ai/free/en/authors/jian-li/)

## 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/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/)
- [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/): [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/)

Updated 1 November 2026
