--- title: "Chase Blagden — author profile and papers — Elamur Research" description: "Chase Blagden: 3 papers on Elamur Research (2024–2025) — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/chase-blagden/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/chase-blagden/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Chase Blagden # Chase Blagden Chase Blagden has 3 papers in our library, in 2024–2025, 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/), [Dakota Mahan](https://md.research.elamur.ai/free/en/authors/dakota-mahan/), [Duy Phung](https://md.research.elamur.ai/free/en/authors/duy-phung/). 3 papers in our library · 2024–2025 No OpenAlex profile matched yet. [📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/chase-blagden/#papers) · [🔗 Cited 146 times in our library](https://md.research.elamur.ai/free/en/authors/chase-blagden/cited-by/) · [⭐ Paper Stars ranking: #7478](https://md.research.elamur.ai/free/en/paper-stars/page/75/#star-7478) 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=Chase+Blagden) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Chase+Blagden) · [dblp](https://dblp.org/search?q=Chase+Blagden) · [ACL Anthology](https://aclanthology.org/search/?q=Chase+Blagden) ## 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 · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 3 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/) · [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/chase-blagden/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/chase-blagden/year/2024/) ## Papers The most cited first (OpenAlex and our library). 1. **[Generative Reward Models](https://md.research.elamur.ai/free/en/papers/mahan-2024-generative-reward-models/)** *(2024 · 58 citations)* Reward models trained with the Bradley-Terry objective on human preference pairs score well on familiar data but generalize poorly to unseen tasks. 2. **[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… 3. **[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 of 13 co-authors with a page, the most papers together first. - [Alon Albalak](https://md.research.elamur.ai/free/en/authors/alon-albalak/) ×3 - [Dakota Mahan](https://md.research.elamur.ai/free/en/authors/dakota-mahan/) ×3 - [Duy Phung](https://md.research.elamur.ai/free/en/authors/duy-phung/) ×3 - [Louis Castricato](https://md.research.elamur.ai/free/en/authors/louis-castricato/) ×3 - [Nathan Lile](https://md.research.elamur.ai/free/en/authors/nathan-lile/) ×3 - [Rafael Rafailov](https://md.research.elamur.ai/free/en/authors/rafael-rafailov/) ×3 - [Anikait Singh](https://md.research.elamur.ai/free/en/authors/anikait-singh/) ×2 - [Jan-Philipp Franken](https://md.research.elamur.ai/free/en/authors/jan-philipp-franken/) ×2 - [Kanishk Gandhi](https://md.research.elamur.ai/free/en/authors/kanishk-gandhi/) ×2 - [Violet Xiang](https://md.research.elamur.ai/free/en/authors/violet-xiang/) ×2 - [Charlie Snell](https://md.research.elamur.ai/free/en/authors/charlie-snell/) - [Chelsea Finn](https://md.research.elamur.ai/free/en/authors/chelsea-finn/) ## Cited by Papers of our library cite their works 146 times (of the 149,439 papers whose bibliographies we read); [62 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/chase-blagden/cited-by/). Updated 3 November 2026