--- title: "Yuexiang Xie · Alibaba Group — author profile and papers" description: "Yuexiang Xie, Alibaba Group: 2 papers on Elamur Research (2025–2026), h-index 1 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/yuexiang-xie/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yuexiang-xie/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yuexiang Xie # Yuexiang Xie Yuexiang Xie has 2 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Bolin Ding](https://md.research.elamur.ai/free/en/authors/bolin-ding/), [Jinyang Gao](https://md.research.elamur.ai/free/en/authors/jinyang-gao/), [Yaliang Li](https://md.research.elamur.ai/free/en/authors/yaliang-li/). 2 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5139810175) · [**h-index 1**](https://openalex.org/authors/A5139810175) · [1 works](https://openalex.org/works?filter=author.id:A5139810175) · [1 citations](https://openalex.org/works?filter=author.id:A5139810175&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yuexiang-xie/#papers) · [🔗 Cited 11 times in our library](https://md.research.elamur.ai/free/en/authors/yuexiang-xie/cited-by/) · [⭐ Paper Stars ranking: #9647](https://md.research.elamur.ai/free/en/paper-stars/page/97/#star-9647) 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=Yuexiang+Xie) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yuexiang+Xie) · [dblp](https://dblp.org/search?q=Yuexiang+Xie) · [ACL Anthology](https://aclanthology.org/search/?q=Yuexiang+Xie) ## Affiliations [🏢**Alibaba Group** Hangzhou · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/alibaba-group/) 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 4 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/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 1 paper](https://md.research.elamur.ai/free/en/authors/yuexiang-xie/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/yuexiang-xie/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[Language Adaptation of Large Language Models: An Empirical Study on LLaMA2](https://md.research.elamur.ai/free/en/papers/wang-2025-language-adaptation-large-language-models/)** *(2025 · 7 citations)* Most large language models learn mainly from English text and handle other languages less well. Building a balanced multilingual model from scratch is too costly for most groups, so adapting an existing model is the practical alternative. Methods for transferring older models such as BERT across languages may not… 2. **[Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/yu-2026-agentic-memory-learning-unified-long/)** *(2026 · 6 citations)* LLM agents working on long, multi-step tasks are limited by finite context windows. Prior approaches handled the two memory types, long-term memory (LTM) and short-term memory (STM), in isolated components, governed by fixed rules, schedules, or an extra expert controller model. AgeMem (Agentic Memory) merges both… ## Co-authors here 4 co-authors with a page, the most papers together first. - [Bolin Ding](https://md.research.elamur.ai/free/en/authors/bolin-ding/) - [Jinyang Gao](https://md.research.elamur.ai/free/en/authors/jinyang-gao/) - [Yaliang Li](https://md.research.elamur.ai/free/en/authors/yaliang-li/) - [Yi Yu](https://md.research.elamur.ai/free/en/authors/yi-yu/) ## 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/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/): [COLING 2025](https://md.research.elamur.ai/free/en/venues/coling/2025/) ## Cited by Papers of our library cite their works 11 times (of the 149,439 papers whose bibliographies we read); [1 citing paper with a page here →](https://md.research.elamur.ai/free/en/authors/yuexiang-xie/cited-by/). Updated 31 October 2026