--- title: "Chao Xue · UNSW Sydney — author profile and papers" description: "Chao Xue, UNSW Sydney: 4 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/chao-xue/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/chao-xue/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Chao Xue # Chao Xue Chao Xue has 4 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Chenyao Lu](https://md.research.elamur.ai/free/en/authors/chenyao-lu/), [Di Liang](https://md.research.elamur.ai/free/en/authors/di-liang/), [Haibo Shi](https://md.research.elamur.ai/free/en/authors/haibo-shi/). 4 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139816698) · [**h-index 0**](https://openalex.org/authors/A5139816698) · [4 works](https://openalex.org/works?filter=author.id:A5139816698) · [0 citations](https://openalex.org/works?filter=author.id:A5139816698&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/chao-xue/#papers) · [🔗 Cited 15 times in our library](https://md.research.elamur.ai/free/en/authors/chao-xue/cited-by/) · [⭐ Paper Stars ranking: #9320](https://md.research.elamur.ai/free/en/paper-stars/page/94/#star-9320) 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=Chao+Xue) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Chao+Xue) · [dblp](https://dblp.org/search?q=Chao+Xue) · [ACL Anthology](https://aclanthology.org/search/?q=Chao+Xue) ## Affiliations [🎓**UNSW Sydney** Sydney · Australia 2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/unsw-sydney/) 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 7 The field of science this work belongs to (OpenAlex fields).[Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 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/) · [Decision Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/) · [Management Science and Operations Research · 1 work](https://md.research.elamur.ai/free/en/shelves/decision-sciences/management-science-and-operations-research/) 🧭 Topics 2 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/chao-xue/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/)** *(2026 · 8 citations)* Generative reward models (GRMs) judge LLM outputs using chain-of-thought (CoT) reasoning. They have two weaknesses. They spend reasoning effort on every input, including easy ones. They also pick among sampled reasoning chains by voting, which cannot separate sound chains from ones that only look convincing. The… 2. **[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/)** *(2026 · 6 citations)* Supervised fine-tuning (SFT) is usually treated as a reliable way to specialize LLMs. The authors show, however, that converged models still get part of their own training set wrong. They call this the Incomplete Learning Phenomenon (ILP), distinguish it from catastrophic forgetting and machine unlearning, and… 3. **[Beyond Token Length: Step Pruner for Efficient and Accurate Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-token-length-step-pruner/)** *(2026 · 2 citations)* Large Reasoning Models often "overthink," producing very long chains of thought even for trivial questions. 4. **[Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling](https://md.research.elamur.ai/free/en/papers/wang-2026-universally-empowering-zeroth-order-optimization/)** *(2026)* Zeroth-Order (ZO) fine-tuning of LLMs needs only forward passes and therefore uses about as much memory as inference. ## Co-authors here 12 of 17 co-authors with a page, the most papers together first. - [Chenyao Lu](https://md.research.elamur.ai/free/en/authors/chenyao-lu/) ×2 - [Di Liang](https://md.research.elamur.ai/free/en/authors/di-liang/) ×2 - [Haibo Shi](https://md.research.elamur.ai/free/en/authors/haibo-shi/) ×2 - [Lei Jiang](https://md.research.elamur.ai/free/en/authors/lei-jiang/) ×2 - [Mengqiao Liu](https://md.research.elamur.ai/free/en/authors/mengqiao-liu/) ×2 - [Peiyang Liu](https://md.research.elamur.ai/free/en/authors/peiyang-liu/) ×2 - [Shuang Liang](https://md.research.elamur.ai/free/en/authors/shuang-liang/) ×2 - [Xianjie Wu](https://md.research.elamur.ai/free/en/authors/xianjie-wu/) ×2 - [Xingsheng Han](https://md.research.elamur.ai/free/en/authors/xingsheng-han/) ×2 - [Yao Wang](https://md.research.elamur.ai/free/en/authors/yao-wang/) ×2 - [Yu Lu](https://md.research.elamur.ai/free/en/authors/yu-lu/) ×2 - [Fei Wang](https://md.research.elamur.ai/free/en/authors/fei-wang/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×3: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×3 - [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/) ## Cited by Papers of our library cite their works 15 times (of the 149,439 papers whose bibliographies we read); [6 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/chao-xue/cited-by/). Updated 1 November 2026