--- title: "Violet Xiang · Stanford University — author profile and papers" description: "Violet Xiang, Stanford University: 2 papers on Elamur Research (2025), h-index 5 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/violet-xiang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/violet-xiang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Violet Xiang # Violet Xiang Violet Xiang has 2 papers in our library, in 2025, 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 [Alon Albalak](https://md.research.elamur.ai/free/en/authors/alon-albalak/), [Anikait Singh](https://md.research.elamur.ai/free/en/authors/anikait-singh/), [Chase Blagden](https://md.research.elamur.ai/free/en/authors/chase-blagden/). 2 papers in our library · 2025 [OpenAlex](https://openalex.org/A5023185054) · [ORCID](https://orcid.org/0000-0002-1584-6231) · [**h-index 5**](https://openalex.org/authors/A5023185054) · [19 works](https://openalex.org/works?filter=author.id:A5023185054) · [74 citations](https://openalex.org/works?filter=author.id:A5023185054&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/violet-xiang/#papers) · [🔗 Cited 88 times in our library](https://md.research.elamur.ai/free/en/authors/violet-xiang/cited-by/) · [⭐ Paper Stars ranking: #8636](https://md.research.elamur.ai/free/en/paper-stars/page/87/#star-8636) 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=Violet+Xiang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Violet+Xiang) · [dblp](https://dblp.org/search?q=Violet+Xiang) · [ACL Anthology](https://aclanthology.org/search/?q=Violet+Xiang) ## Affiliations [🎓**Stanford University** Stanford · United States 2022–2026 · 15 papers*current*](https://md.research.elamur.ai/free/en/universities/stanford-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed. ## 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).[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/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Applied Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/applied-mathematics/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) 🧭 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/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/violet-xiang/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/xiang-2025-towards-system-2-reasoning-llms/)** *(2025 · 47 citations)* Large language models handle routine math well but still fail on harder problems. The authors argue that ordinary Chain-of-Thought (CoT) is part of the cause. Written solutions in training data show only the polished final derivation. They omit the hidden, non-linear work of trying options, checking them and… 2. **[Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models](https://md.research.elamur.ai/free/en/papers/albalak-2025-big-math-large-scale-high/)** *(2025 · 43 citations)* Reinforcement learning for reasoning in LLMs needs math problems whose answers can be checked automatically. ## Co-authors here 12 co-authors with a page, the most papers together first. - [Alon Albalak](https://md.research.elamur.ai/free/en/authors/alon-albalak/) ×2 - [Anikait Singh](https://md.research.elamur.ai/free/en/authors/anikait-singh/) ×2 - [Chase Blagden](https://md.research.elamur.ai/free/en/authors/chase-blagden/) ×2 - [Dakota Mahan](https://md.research.elamur.ai/free/en/authors/dakota-mahan/) ×2 - [Duy Phung](https://md.research.elamur.ai/free/en/authors/duy-phung/) ×2 - [Kanishk Gandhi](https://md.research.elamur.ai/free/en/authors/kanishk-gandhi/) ×2 - [Louis Castricato](https://md.research.elamur.ai/free/en/authors/louis-castricato/) ×2 - [Nathan Lile](https://md.research.elamur.ai/free/en/authors/nathan-lile/) ×2 - [Rafael Rafailov](https://md.research.elamur.ai/free/en/authors/rafael-rafailov/) ×2 - [Charlie Snell](https://md.research.elamur.ai/free/en/authors/charlie-snell/) - [Jan-Philipp Franken](https://md.research.elamur.ai/free/en/authors/jan-philipp-franken/) - [Nick Haber](https://md.research.elamur.ai/free/en/authors/nick-haber/) ## Cited by Papers of our library cite their works 88 times (of the 149,439 papers whose bibliographies we read); [40 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/violet-xiang/cited-by/). Updated 3 November 2026