--- title: "Hui Xue — author profile and papers — Elamur Research" description: "Hui Xue, Alibaba Group: 5 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/hui-xue/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hui-xue/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Hui Xue # Hui Xue Hui Xue has 5 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Haiwen Hong](https://md.research.elamur.ai/free/en/authors/haiwen-hong/), [Longtao Huang](https://md.research.elamur.ai/free/en/authors/longtao-huang/), [Huajun Chen](https://md.research.elamur.ai/free/en/authors/huajun-chen/). 5 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139731032) · [**h-index 1**](https://openalex.org/authors/A5139731032) · [4 works](https://openalex.org/works?filter=author.id:A5139731032) · [1 citations](https://openalex.org/works?filter=author.id:A5139731032&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/hui-xue/#papers) · [🔗 Cited 3 times in our library](https://md.research.elamur.ai/free/en/authors/hui-xue/cited-by/) · [⭐ Paper Stars ranking: #11897](https://md.research.elamur.ai/free/en/paper-stars/page/119/#star-11897) 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=Hui+Xue) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Hui+Xue) · [dblp](https://dblp.org/search?q=Hui+Xue) · [ACL Anthology](https://aclanthology.org/search/?q=Hui+Xue) ## Affiliations [🏢**Alibaba Group** Hangzhou · China 2026 · 3 papers*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 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 5 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 5 Research subjects and languages the work is about.[Language models & pretraining · 4 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Bias, fairness & safety · 2 works](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 5 papers](https://md.research.elamur.ai/free/en/authors/hui-xue/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework](https://md.research.elamur.ai/free/en/papers/weng-2026-safe-sail-fine-grained-safety/)** *(2026 · 2 citations)* Sparse autoencoders (SAEs) can split a model's tangled activations into interpretable features. However, safety concepts are rare in typical data, and it is unclear which SAE setups produce fine-grained safety features. Explaining every feature is also expensive. Safe-SAIL is a three-stage pipeline (SAE training… 2. **[Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/xu-2026-seeing-but-not-thinking-routing/)** *(2026 · 1 citation)* The paper examines a failure mode in multimodal Mixture-of-Experts (MoE) vision-language models. The authors call it "Seeing but Not Thinking": a model reads an image-rendered problem correctly but then reasons wrongly, even though it solves the same problem when given as text. Using image-rendered versions of… 3. **[Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics](https://md.research.elamur.ai/free/en/papers/xu-2026-why-steering-works-unified-view/)** *(2026 · 1 citation)* Methods for controlling LLM behaviour are usually studied separately, with different assumptions and evaluation setups. 4. **[How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities](https://md.research.elamur.ai/free/en/papers/xu-2026-how-controllable-are-large-language/)** *(2026)* LLMs used in sensitive settings can drift in intent, tone, or persona. Existing steering benchmarks cover isolated behaviors, define concepts inconsistently, and ignore how specific a control target is. The authors propose SteerEval, a benchmark that crosses three behavioral domains (language features, sentiment… 5. **[LASA: Language-Agnostic Semantic Alignment at the Semantic Bottleneck for LLM Safety](https://md.research.elamur.ai/free/en/papers/yang-2026-lasa-language-agnostic-semantic-alignment/)** *(2026)* LLMs tend to refuse harmful requests reliably in high-resource languages but are much easier to jailbreak in low-resource ones. ## Co-authors here 12 of 25 co-authors with a page, the most papers together first. - [Haiwen Hong](https://md.research.elamur.ai/free/en/authors/haiwen-hong/) ×3 - [Longtao Huang](https://md.research.elamur.ai/free/en/authors/longtao-huang/) ×3 - [Huajun Chen](https://md.research.elamur.ai/free/en/authors/huajun-chen/) ×2 - [Jialing Tao](https://md.research.elamur.ai/free/en/authors/jialing-tao/) ×2 - [Jiaqi Weng](https://md.research.elamur.ai/free/en/authors/jiaqi-weng/) ×2 - [Ningyu Zhang](https://md.research.elamur.ai/free/en/authors/ningyu-zhang/) ×2 - [Shumin Deng](https://md.research.elamur.ai/free/en/authors/shumin-deng/) ×2 - [Yongliang Shen](https://md.research.elamur.ai/free/en/authors/yongliang-shen/) ×2 - [Zhixuan Chu](https://md.research.elamur.ai/free/en/authors/zhixuan-chu/) ×2 - [Ziwen Xu](https://md.research.elamur.ai/free/en/authors/ziwen-xu/) ×2 - [Chenyan WU](https://md.research.elamur.ai/free/en/authors/chenyan-wu/) - [Han Qiu](https://md.research.elamur.ai/free/en/authors/han-qiu/) ## 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/) ×4: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×4 - [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/) ## Cited by Papers of our library cite their works 3 times (of the 149,439 papers whose bibliographies we read); [3 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/hui-xue/cited-by/). Updated 2 November 2026