--- title: "Rui Song · Jilin University — author profile and papers" description: "Rui Song, Jilin University: 2 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/rui-song/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/rui-song/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Rui Song # Rui Song Rui Song 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/), [Yingji Li](https://md.research.elamur.ai/free/en/authors/yingji-li/), [Fausto Giunchiglia](https://md.research.elamur.ai/free/en/authors/fausto-giunchiglia/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139813399) · [**h-index 1**](https://openalex.org/authors/A5139813399) · [8 works](https://openalex.org/works?filter=author.id:A5139813399) · [1 citations](https://openalex.org/works?filter=author.id:A5139813399&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/rui-song/#papers) · [2 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #12203](https://md.research.elamur.ai/free/en/paper-stars/page/123/#star-12203) 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=Rui+Song) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Rui+Song) · [dblp](https://dblp.org/search?q=Rui+Song) · [ACL Anthology](https://aclanthology.org/search/?q=Rui+Song) ## Affiliations [🎓**Jilin University** Changchun · China 2026 · 7 papers*current*](https://md.research.elamur.ai/free/en/universities/jilin-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## 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/rui-song/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 4 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* 4. **[ACSE: An Ancient Character Semantic-Aware Embedding for Large Language Models ↗](https://aclanthology.org/2026.findings-acl.437/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Zhihan Zhou 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 - [Yingji Li](https://md.research.elamur.ai/free/en/authors/yingji-li/) ×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/) - Findings of the Association for Computational Linguistics: ACL 2026 Updated 1 November 2026